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Jan Benhelm

CMO at Zurich Instruments Ltd

amplifier, automation, bandwidth (signal processing), blue box, booting, computer, computer hardware, computing, digitization, electric generator, electrical engineering, engineering, filter (signal processing), goal, intermediate frequency, latency (engineering), low-pass filter, quantum computing, real-time computing, signal generator, software , software framework, spectral density, spectrum, spectrum analyzer

Sadik Hafizovic

CEO & Co-founder at Zurich Instruments Ltd

amplifier, automation, bandwidth (signal processing), blue box, booting, computer, computer hardware, computing, digitization, electric generator, electrical engineering, engineering, filter (signal processing), goal, intermediate frequency, latency (engineering), low-pass filter, quantum computing, real-time computing, signal generator, software , software framework, spectral density, spectrum, spectrum analyzer

Austin Minnich

Professor at Caltech

atom, campaign: quantum symposium, coherence (physics), condensed matter physics, coupling constant, electronic correlation, energy, energy level, excited state, google, google quantum, google quantum ai, google quantum ai tutorial, matter, molecule, physics, pi, pr_pr: quantum, purpose: inform, quantum, quantum chemistry, quantum computing, quantum simulator, quantum summer symposium, quantum summer symposium 2021, quantum supremacy, quantum symposium, series: quantum symposium, signal, spectral density, spin (physics), superconductivity, temperature, time, topological order, topology, type: upload only, unitarity (physics), what is google quantum ai

Gianluigi Botton

Science Director at Canadian Light Source Inc.

artificial intelligence, artificial neural network, autoencoder, charge-coupled device, codec, convolutional neural network, data compression, data science, deconvolution, deep learning, digitization, distortion, electron, electron microscope, image segmentation, machine learning, microscope, modulation, noise reduction, photonics, python 2021, python tutorial, science, science research, scipy library, scipy tools, scipy tutorial, signal, software engineering, spectral density, spectroscopy, spectrum, statistical classification, statistics, transmission electron microscopy

Alexandre Pofelski

Postdoctoral Researcher at McMaster University

artificial intelligence, artificial neural network, autoencoder, charge-coupled device, codec, convolutional neural network, data compression, data science, deconvolution, deep learning, digitization, distortion, electron, electron microscope, image segmentation, machine learning, microscope, modulation, noise reduction, photonics, python 2021, python tutorial, science, science research, scipy library, scipy tools, scipy tutorial, signal, software engineering, spectral density, spectroscopy, spectrum, statistical classification, statistics, transmission electron microscopy

Shayan Mousavi s

Research Assistant at anadian Center of Electron Microscopy

artificial intelligence, artificial neural network, autoencoder, charge-coupled device, codec, convolutional neural network, data compression, data science, deconvolution, deep learning, digitization, distortion, electron, electron microscope, image segmentation, machine learning, microscope, modulation, noise reduction, photonics, python 2021, python tutorial, science, science research, scipy library, scipy tools, scipy tutorial, signal, software engineering, spectral density, spectroscopy, spectrum, statistical classification, statistics, transmission electron microscopy

Jan Jongboom

Developer Evangelist IoT at ARM

machine learning approaches, accelerometer, accuracy and precision, algorithm, alphago, altitude, android (operating system), anomaly detection, artificial intelligence, artificial intelligence 2020, artificial neural network, atmospheric pressure, central processing unit, cloud computing, cluster analysis, computer, computer data storage, computer network, computer science, computer science 2021, computer science event, computer science event 2021, convolution, convolutional neural network, correlation and dependence, data compression, deep learning, deepmind, email, embedded system, encryption, engineering, filter (signal processing), future, graph (abstract data type), hyperparameter (machine learning), information technology conference , innovation, intel, intelligence, internet, iot, k-means clustering, keyboard technology, language, latency (engineering), lawyer, learning, learning rate, lora, lorawan, low-pass filter, machine learning, machine learning 2020, machine learning 2021, machine learning techniques, machine learning technologie, machine learning technologies , machine learning tools, map, microsoft, microsoft windows, network, network optimization , neural network, of, parameter, perception, pipeline (computing), pixel, plug and play, prediction, random-access memory, raster graphics, read-only memory, reason, recurrent neural network, sears, sensor, signal, signal processing, spectral density, switch, talk by peter schulmeyer, tax, technologie, the, thermometer, things, tinyml conference 2020, tinyml foundation, tinyml talks 2021, tinyml2021, tinyml2021 talk, ttn, tuner (radio), walt disney world, water

Anthony Joseph

Chief Technology Officer at My House Geek

accelerometer, attention, bit, bluetooth, bluetooth low energy, boxing, cloud computing, computer, computer science, computer science 2020, data collection, face, feedback, glass, god, halloween, information, information technology conference , luck, machine, machine learning, machine learning tutorials, pleasure, smoke, spectral density, technology, tinyml asia 2020, tinyml foundation, video, video game, wearable technology

Liang Zhang

Global Sales Strategy & Operations at LinkedIn

before deep learning , artificial intelligence , artificial intelligence tutorial, computer science conference , feed and ads modeling, introduction to multimedia, visio-lingual representations, 3d cnns, accent (sociolinguistics), accuracy and precision, acm 2020 tutorial, acoustic model, action recognition, ads recommendation, advertising, algorithm, angle, apache hadoop, apache spark, api, application software, applications at linkedin, array data structure, array data type, art, artificial intelligence tutorial, artificial neural network, assembly language, association for computing machinery, attention, attention (machine learning), average, baby talk, bag-of-words model, bangalore, beef, before deep learning , bible, bichon frise, cartesian coordinate system, castle, central processing unit, click-through rate, closed captioning, code-division multiple access, codec, coherence (physics), color, common technologies for feed and ads recommendation, compass, computer, computer graphics, computer performance, computer science tutorial, computer science tutorials, computer vision, computer vision 2020, computing, concept, convolution, convolutional neural network, cosine similarity, data, data compression, data conversion, data science tutorial, data type, debugging, deconvolution, deep learning, deep learning and cnns, deep learnning, deep learnning tutorial, definition, depiction, design, desk, diagram, diamond, digital image processing, dimension, dsgmm and deep cluster-and-aggregate method, dynamic programming, education, email spam, energy, engine, enzyme kinetics, equation, essay, euclidean vector, experiment, extract, transform, load, feature (machine learning), feature extraction, feature learning, feed recommendation , file system, film frame, finite set, function (mathematics), gas, gender, gradient, grayscale, hidden markov model, histogram, history, hyperparameter optimization, image embeddings, image representations , image segmentation, image understanding, imagenet, improvements on 3d cnn, improvements on 3d cnns and two-stream, infection, information, information retrieval, input/output, inspection, instagram, intelligence, interface (computing), internet, introduction - feed, ads, search and spam, inverted index, k-means clustering, kdd2020 tutorials, language, language model, learning, lecture-style tutorials, letter case, library (computing), likelihood function, linear combination, linearity, linkedin, literature, loader (computing), logic, long short-term memory, machine, machine learning, map, markov chain, markov model, mathematical optimization, matrix (mathematics), mean, meme, memory, metric learning for images, metric space, microsoft, mixture model, mobile app, monotonic function, motivation, moving average, mp3, multimedia, multimedia infrastructure, multimedia search, multimodality, multivariate random variable, music, nature, navigation, neural network, news, non-local networks and slowfast, nothing, number, object detection, online and offline, optical character recognition, optical flow, optimization for cnns, oracle corporation, parameter, parameter (computer programming), parity bit, phoneme, pixel, plasterwork, podcast, precision and recall, prediction, preprocessor, protein–protein interaction, python (programming language), radio, reason, recommender system, recurrent neural network, research, robust statistics, satya nadella, search algorithm, search engine, search engine indexing, self-supervised learning, self-supervised video embeddings, sense, signal, similarity learning, simulation, sms, social media, social networking service, softmax function, software , source lines of code, space, spam detection, spamming, spectral density, spectrogram, speech, speech recognition, speech technologies for video understanding, spotify, statistical classification, statistics, streaming media, string (computer science), subroutine, summation, supervised learning, support-vector machine, temporal topic localization, tensor, texas, three-dimensional space, training, validation, and test sets, transcription (linguistics), transformer (machine learning model), transmission (mechanics), truck, two-stream networks, typing, understanding, unsupervised learning, upload, use case, variance, vector graphics, vector space, video, video captioning, video classification, video embeddings and networks, video game, video game console, video game live streaming, video representations used in production, video search, video search engine, video understanding, weight, youtube

Di Wen

Staff Software Engineer at LinkedIn

before deep learning , artificial intelligence , artificial intelligence tutorial, computer science conference , feed and ads modeling, introduction to multimedia, visio-lingual representations, 3d cnns, accent (sociolinguistics), accuracy and precision, acm 2020 tutorial, acoustic model, action recognition, ads recommendation, advertising, algorithm, angle, apache hadoop, api, application software, applications at linkedin, art, artificial intelligence tutorial, artificial neural network, association for computing machinery, attention, attention (machine learning), average, baby talk, bag-of-words model, bangalore, beef, before deep learning , bible, bichon frise, cartesian coordinate system, castle, central processing unit, click-through rate, closed captioning, code-division multiple access, codec, coherence (physics), common technologies for feed and ads recommendation, compass, computer, computer graphics, computer performance, computer science tutorial, computer science tutorials, computer vision, computer vision 2020, computing, concept, convolution, convolutional neural network, cosine similarity, data, data compression, data science tutorial, deconvolution, deep learning, deep learning and cnns, deep learnning, deep learnning tutorial, definition, depiction, design, desk, diagram, diamond, digital image processing, dimension, dsgmm and deep cluster-and-aggregate method, dynamic programming, education, email spam, energy, engine, enzyme kinetics, equation, essay, euclidean vector, experiment, extract, transform, load, feature (machine learning), feature extraction, feature learning, feed recommendation , film frame, finite set, function (mathematics), gas, gender, gradient, grayscale, hidden markov model, histogram, history, hyperparameter optimization, image embeddings, image representations , image segmentation, image understanding, imagenet, improvements on 3d cnn, improvements on 3d cnns and two-stream, infection, information, information retrieval, input/output, inspection, instagram, intelligence, interface (computing), internet, introduction - feed, ads, search and spam, inverted index, k-means clustering, kdd2020 tutorials, language, language model, learning, lecture-style tutorials, letter case, likelihood function, linear combination, linearity, linkedin, literature, logic, long short-term memory, machine, machine learning, map, markov chain, markov model, mathematical optimization, matrix (mathematics), mean, meme, memory, metric learning for images, metric space, microsoft, mixture model, mobile app, monotonic function, motivation, moving average, mp3, multimedia, multimedia infrastructure, multimedia search, multimodality, multivariate random variable, music, nature, navigation, neural network, news, non-local networks and slowfast, nothing, number, object detection, online and offline, optical character recognition, optical flow, optimization for cnns, oracle corporation, parameter, parity bit, phoneme, pixel, plasterwork, podcast, precision and recall, prediction, protein–protein interaction, radio, reason, recommender system, recurrent neural network, research, robust statistics, satya nadella, search algorithm, search engine, search engine indexing, self-supervised learning, self-supervised video embeddings, sense, signal, similarity learning, simulation, sms, social media, social networking service, softmax function, software , space, spam detection, spamming, spectral density, spectrogram, speech, speech recognition, speech technologies for video understanding, spotify, statistical classification, statistics, streaming media, summation, supervised learning, support-vector machine, temporal topic localization, texas, three-dimensional space, transcription (linguistics), transmission (mechanics), truck, two-stream networks, typing, understanding, unsupervised learning, upload, use case, variance, vector graphics, vector space, video, video captioning, video classification, video embeddings and networks, video game, video game console, video game live streaming, video representations used in production, video search, video search engine, video understanding, weight, youtube

Yijie Dylan Wang

Software Engineering Manager at LinkedIn

before deep learning , artificial intelligence , artificial intelligence tutorial, computer science conference , feed and ads modeling, introduction to multimedia, visio-lingual representations, 3d cnns, accent (sociolinguistics), accuracy and precision, acm 2020 tutorial, acoustic model, action recognition, advertising, algorithm, angle, apache hadoop, api, application software, applications at linkedin, art, artificial intelligence tutorial, artificial neural network, association for computing machinery, attention, attention (machine learning), average, baby talk, bag-of-words model, bangalore, beef, before deep learning , bible, bichon frise, cartesian coordinate system, castle, central processing unit, closed captioning, code-division multiple access, codec, coherence (physics), compass, computer, computer graphics, computer performance, computer science tutorial, computer science tutorials, computer vision, computer vision 2020, computing, concept, convolution, convolutional neural network, data, data compression, data science tutorial, deconvolution, deep learning, deep learning and cnns, deep learnning, deep learnning tutorial, definition, depiction, design, desk, diagram, diamond, digital image processing, dimension, dsgmm and deep cluster-and-aggregate method, dynamic programming, education, email spam, energy, engine, enzyme kinetics, equation, essay, euclidean vector, experiment, extract, transform, load, feature (machine learning), feature extraction, feature learning, film frame, function (mathematics), gas, gender, gradient, grayscale, hidden markov model, histogram, history, hyperparameter optimization, image embeddings, image representations , image segmentation, imagenet, improvements on 3d cnn, improvements on 3d cnns and two-stream, infection, information, information retrieval, input/output, inspection, instagram, intelligence, interface (computing), internet, inverted index, k-means clustering, kdd2020 tutorials, language, language model, learning, lecture-style tutorials, likelihood function, linearity, linkedin, literature, long short-term memory, machine, machine learning, map, markov chain, markov model, mathematical optimization, matrix (mathematics), mean, meme, memory, metric learning for images, metric space, microsoft, mixture model, mobile app, monotonic function, motivation, moving average, mp3, multimedia, multimedia infrastructure, multimodality, music, nature, navigation, neural network, news, non-local networks and slowfast, nothing, number, object detection, online and offline, optical character recognition, optical flow, optimization for cnns, oracle corporation, parameter, parity bit, phoneme, pixel, plasterwork, podcast, precision and recall, prediction, protein–protein interaction, radio, reason, recommender system, recurrent neural network, research, robust statistics, satya nadella, search algorithm, search engine, search engine indexing, self-supervised learning, self-supervised video embeddings, sense, signal, similarity learning, sms, social networking service, softmax function, space, spam detection, spamming, spectral density, spectrogram, speech, speech recognition, speech technologies for video understanding, spotify, statistical classification, statistics, streaming media, supervised learning, support-vector machine, temporal topic localization, texas, three-dimensional space, transcription (linguistics), transmission (mechanics), truck, two-stream networks, typing, understanding, unsupervised learning, upload, use case, variance, vector graphics, vector space, video, video captioning, video classification, video embeddings and networks, video game, video game console, video game live streaming, video search, video search engine, video understanding, weight, youtube

Bharat Jain

Data Scientist at LinkedIn

before deep learning , artificial intelligence , artificial intelligence tutorial, computer science conference , feed and ads modeling, introduction to multimedia, visio-lingual representations, 3d cnns, accent (sociolinguistics), accuracy and precision, acm 2020 tutorial, acoustic model, action recognition, ads recommendation, advertising, algorithm, angle, apache hadoop, api, application software, applications at linkedin, art, artificial intelligence tutorial, artificial neural network, association for computing machinery, attention, attention (machine learning), average, baby talk, bag-of-words model, bangalore, beef, before deep learning , bible, bichon frise, cartesian coordinate system, castle, central processing unit, click-through rate, closed captioning, code-division multiple access, codec, coherence (physics), common technologies for feed and ads recommendation, compass, computer, computer graphics, computer performance, computer science tutorial, computer science tutorials, computer vision, computer vision 2020, computing, concept, convolution, convolutional neural network, cosine similarity, data, data compression, data science tutorial, deconvolution, deep learning, deep learning and cnns, deep learnning, deep learnning tutorial, definition, depiction, design, desk, diagram, diamond, digital image processing, dimension, dsgmm and deep cluster-and-aggregate method, dynamic programming, education, email spam, energy, engine, enzyme kinetics, equation, essay, euclidean vector, experiment, extract, transform, load, feature (machine learning), feature extraction, feature learning, feed recommendation , film frame, finite set, function (mathematics), gas, gender, gradient, grayscale, hidden markov model, histogram, history, hyperparameter optimization, image embeddings, image representations , image segmentation, image understanding, imagenet, improvements on 3d cnn, improvements on 3d cnns and two-stream, infection, information, information retrieval, input/output, inspection, instagram, intelligence, interface (computing), internet, introduction - feed, ads, search and spam, inverted index, k-means clustering, kdd2020 tutorials, language, language model, learning, lecture-style tutorials, letter case, likelihood function, linear combination, linearity, linkedin, literature, logic, long short-term memory, machine, machine learning, map, markov chain, markov model, mathematical optimization, matrix (mathematics), mean, meme, memory, metric learning for images, metric space, microsoft, mixture model, mobile app, monotonic function, motivation, moving average, mp3, multimedia, multimedia infrastructure, multimedia search, multimodality, multivariate random variable, music, nature, navigation, neural network, news, non-local networks and slowfast, nothing, number, object detection, online and offline, optical character recognition, optical flow, optimization for cnns, oracle corporation, parameter, parity bit, phoneme, pixel, plasterwork, podcast, precision and recall, prediction, protein–protein interaction, radio, reason, recommender system, recurrent neural network, research, robust statistics, satya nadella, search algorithm, search engine, search engine indexing, self-supervised learning, self-supervised video embeddings, sense, signal, similarity learning, simulation, sms, social media, social networking service, softmax function, software , space, spam detection, spamming, spectral density, spectrogram, speech, speech recognition, speech technologies for video understanding, spotify, statistical classification, statistics, streaming media, summation, supervised learning, support-vector machine, temporal topic localization, texas, three-dimensional space, transcription (linguistics), transmission (mechanics), truck, two-stream networks, typing, understanding, unsupervised learning, upload, use case, variance, vector graphics, vector space, video, video captioning, video classification, video embeddings and networks, video game, video game console, video game live streaming, video representations used in production, video search, video search engine, video understanding, weight, youtube

Nikita Gupta

Senior Applied Research Engineer at LinkedIn

before deep learning , artificial intelligence , artificial intelligence tutorial, computer science conference , feed and ads modeling, introduction to multimedia, visio-lingual representations, 3d cnns, accent (sociolinguistics), accuracy and precision, acm 2020 tutorial, acoustic model, action recognition, ads recommendation, advertising, algorithm, angle, apache hadoop, api, application software, applications at linkedin, art, artificial intelligence tutorial, artificial neural network, association for computing machinery, attention, attention (machine learning), average, baby talk, bag-of-words model, bangalore, beef, before deep learning , bible, bichon frise, cartesian coordinate system, castle, central processing unit, click-through rate, closed captioning, code-division multiple access, codec, coherence (physics), common technologies for feed and ads recommendation, compass, computer, computer graphics, computer performance, computer science tutorial, computer science tutorials, computer vision, computer vision 2020, computing, concept, convolution, convolutional neural network, cosine similarity, data, data compression, data science tutorial, deconvolution, deep learning, deep learning and cnns, deep learnning, deep learnning tutorial, definition, depiction, design, desk, diagram, diamond, digital image processing, dimension, dsgmm and deep cluster-and-aggregate method, dynamic programming, education, email spam, energy, engine, enzyme kinetics, equation, essay, euclidean vector, experiment, extract, transform, load, feature (machine learning), feature extraction, feature learning, feed recommendation , film frame, finite set, function (mathematics), gas, gender, gradient, grayscale, hidden markov model, histogram, history, hyperparameter optimization, image embeddings, image representations , image segmentation, image understanding, imagenet, improvements on 3d cnn, improvements on 3d cnns and two-stream, infection, information, information retrieval, input/output, inspection, instagram, intelligence, interface (computing), internet, introduction - feed, ads, search and spam, inverted index, k-means clustering, kdd2020 tutorials, language, language model, learning, lecture-style tutorials, letter case, likelihood function, linear combination, linearity, linkedin, literature, logic, long short-term memory, machine, machine learning, map, markov chain, markov model, mathematical optimization, matrix (mathematics), mean, meme, memory, metric learning for images, metric space, microsoft, mixture model, mobile app, monotonic function, motivation, moving average, mp3, multimedia, multimedia infrastructure, multimedia search, multimodality, multivariate random variable, music, nature, navigation, neural network, news, non-local networks and slowfast, nothing, number, object detection, online and offline, optical character recognition, optical flow, optimization for cnns, oracle corporation, parameter, parity bit, phoneme, pixel, plasterwork, podcast, precision and recall, prediction, protein–protein interaction, radio, reason, recommender system, recurrent neural network, research, robust statistics, satya nadella, search algorithm, search engine, search engine indexing, self-supervised learning, self-supervised video embeddings, sense, signal, similarity learning, simulation, sms, social media, social networking service, softmax function, software , space, spam detection, spamming, spectral density, spectrogram, speech, speech recognition, speech technologies for video understanding, spotify, statistical classification, statistics, streaming media, summation, supervised learning, support-vector machine, temporal topic localization, texas, three-dimensional space, transcription (linguistics), transmission (mechanics), truck, two-stream networks, typing, understanding, unsupervised learning, upload, use case, variance, vector graphics, vector space, video, video captioning, video classification, video embeddings and networks, video game, video game console, video game live streaming, video representations used in production, video search, video search engine, video understanding, weight, youtube

Suhit Sinha

Senior Applied Research Engineer at LinkedIn

Sumit Srivastava

Staff Applied Research Engineer at LinkedIn

Sirjan Kafle

Senior Machine Learning Engineer, Multimedia AI at LinkedIn

Aman Gupta

Senior Machine Learning Scientist at LinkedIn Multimedia AI

Ananth Sankar

Principal Staff Engineer at LinkedIn

before deep learning , artificial intelligence , artificial intelligence tutorial, computer science conference , feed and ads modeling, introduction to multimedia, visio-lingual representations, 3d cnns, accent (sociolinguistics), accuracy and precision, acm 2020 tutorial, acoustic model, action recognition, ads recommendation, advertising, ai, algorithm, angle, apache hadoop, api, application software, applications at linkedin, art, artificial intelligence tutorial, artificial neural network, association for computing machinery, attention, attention (machine learning), automatic summarization, average, baby talk, backpropagation, bag-of-words model, bangalore, beef, before deep learning , bible, bichon frise, black box, cartesian coordinate system, castle, central processing unit, click-through rate, closed captioning, code-division multiple access, codec, coherence (physics), common technologies for feed and ads recommendation, compass, computer, computer graphics, computer performance, computer science tutorial, computer science tutorials, computer vision, computer vision 2020, computing, concept, convolution, convolutional neural network, cosine similarity, cross entropy, data, data compression, data science, data science tutorial, deconvolution, deep learning, deep learning and cnns, deep learnning, deep learnning tutorial, definition, depiction, design, desk, diagram, diamond, digital image processing, dimension, dsgmm and deep cluster-and-aggregate method, dynamic programming, education, email spam, encoding (memory), energy, engine, english language, enzyme kinetics, equation, essay, euclidean vector, experiment, extract, transform, load, feature (machine learning), feature extraction, feature learning, feed recommendation , feedforward neural network, film frame, finite set, four-dimensional space, function (mathematics), gas, gender, gradient, grayscale, hidden markov model, histogram, history, hyperparameter optimization, image embeddings, image representations , image segmentation, image understanding, imagenet, improvements on 3d cnn, improvements on 3d cnns and two-stream, infection, information, information retrieval, input/output, inspection, instagram, intelligence, interface (computing), internet, introduction - feed, ads, search and spam, inverted index, k-means clustering, kdd2020 tutorials, language, language model, learning, lecture-style tutorials, letter case, likelihood function, linear combination, linearity, linkedin, literature, logic, long short-term memory, machine, machine learning, map, markov chain, markov model, mathematical optimization, matrix (mathematics), mean, meme, memory, metric learning for images, metric space, microsoft, mind, mixture model, mobile app, monotonic function, motivation, moving average, mp3, multimedia, multimedia infrastructure, multimedia search, multimodality, multivariate random variable, music, natural language processing, nature, navigation, neural network, neural networks, news, non-local networks and slowfast, nothing, number, object detection, odsc, odsc india, online and offline, optical character recognition, optical flow, optimization for cnns, oracle corporation, parameter, parity bit, phoneme, pixel, plasterwork, podcast, precision and recall, prediction, protein–protein interaction, radio, reason, recommender system, recurrent neural network, research, robust statistics, satya nadella, search algorithm, search engine, search engine indexing, self-supervised learning, self-supervised video embeddings, semantics, sense, signal, similarity learning, simulation, sms, social media, social networking service, softmax function, software , space, spam detection, spamming, spectral density, spectrogram, speech, speech recognition, speech technologies for video understanding, spotify, statistical classification, statistics, streaming media, summation, supervised learning, support-vector machine, temporal topic localization, texas, three-dimensional space, transcription (linguistics), transmission (mechanics), truck, two-stream networks, typing, understanding, unsupervised learning, upload, use case, vanishing gradient problem, variance, vector graphics, vector space, video, video captioning, video classification, video embeddings and networks, video game, video game console, video game live streaming, video representations used in production, video search, video search engine, video understanding, vocabulary, weight, youtube

Andrea Goldsmith

Professor at Stanford University

3g, 4g, 5g, 5g world, ai, americas, andrea goldsmith, apac, applied science, artificial intelligence, automation, bias, brain, cellular network, cloud computing, complexity, computational complexity theory, computer network, computer science, culture, data science, data visualization , design, economics, education, emea, engineering, epilepsy, epileptic seizure, expert, extremely high frequency, federal communications commission, information, interdisciplinarity, internet of things, machine learning, mobile phone, mobile technology, multicast, network, privacy, radio, radio receiver, reliability (computer networking), research, science, scientist, signal, small cell, spectral density, spectrum management, standford university, stanford conference, statistics, t-mobile us, technology, transmitter, vehicular automation, virtual reality, wi-fi, wids, wids datathon, wids podcast, wireless sensor network, women in data, women in data science, women in technology, women in technology conference, worldwide

Cheng Shen

Researcher at Peking University

chopper (electronics), clock, ddr3 sdram, detector (radio), electromagnetic radiation, encryption, experiment, false alarm, fax, frequency, hypothesis, medium access control, memory, pulp (tooth), radio, radio telescope, research, software , spectral density, spectrum, stimulus (physiology), visual perception, wi-fi protected access, wireless, youtube

Adam Thompson

Senior Solutions Architect at NVIDIA

__cuda_array_interface__, c (programming language), c++, central processing unit, communications system, computer network, cupy, deep learning, federal communications commission, filter bank, gpu, graphics processing unit, high performance python, internet of things, kernel (operating system), library (computing), lie detection, neural network, numba, numpy, pointer (computer programming), pydata, python, radio, rapids, real-time computing, sampler (musical instrument), scipy signal, shared memory, signal processing, software-defined radio, spectral density, spectrogram, wavelet

Ozan Öktem

Associate Professor at KTH, The Royal Institute of Technology

adolescence, algorithm, applied and computational geometry, applied mathematics, artificial neural network, astronomy , bayesian inference, data science, database, deep learning, deepfake, expected value, function (mathematics), generative adversarial network, internet, inverse problem, loss function, machine learning, math, mathematical optimization, parameter, prior probability, random variable, randomness, reason, simulation and modeling, spectral density, supervised learning, unsupervised learning

Jonathan Saunders

Graduate Student at University of Oregon

artificial neural network, brain, cerebral cortex, convolutional neural network, deep learning, english language, functional magnetic resonance imaging, inhibitory postsynaptic potential, language, nervous system, neural circuit, neuron, neurotransmitter, perception, phoneme, phonetics, spectral density, speech, speech perception, speech recognition, speech synthesis, statistical classification, synapse, synaptic weight, wavenet

Alex Comerford

Data Scientist

artificial neural network, brain, cerebral cortex, convolutional neural network, deep learning, english language, functional magnetic resonance imaging, inhibitory postsynaptic potential, language, nervous system, neural circuit, neuron, neurotransmitter, perception, phoneme, phonetics, spectral density, speech, speech perception, speech recognition, speech synthesis, statistical classification, synapse, synaptic weight, wavenet

George Williams

Director of Data Science at Data Science

artificial neural network, brain, cerebral cortex, convolutional neural network, deep learning, english language, functional magnetic resonance imaging, inhibitory postsynaptic potential, language, nervous system, neural circuit, neuron, neurotransmitter, perception, phoneme, phonetics, spectral density, speech, speech perception, speech recognition, speech synthesis, statistical classification, synapse, synaptic weight, wavenet

Arthur Szlam

Assistant professor of mathematics at The City College of New York

atlas experiment, autoencoder, backpropagation, basis (linear algebra), community structure, computational complexity theory, convolution, curvature, deep learning, density functional theory, euclidean space, fiber bundle, fourier transform, laplace operator, linear algebra, linear combination, matching (graph theory), matrix (mathematics), matrix completion, quantum mechanics, spectral density, tangent bundle, transfer function, travelling salesman problem, wave

Joan Bruna

Assistant Professor at Courant Institute, New York University

atlas experiment, autoencoder, backpropagation, basis (linear algebra), community structure, computational complexity theory, convolution, curvature, deep learning, density functional theory, euclidean space, fiber bundle, fourier transform, laplace operator, linear algebra, linear combination, matching (graph theory), matrix (mathematics), matrix completion, quantum mechanics, spectral density, tangent bundle, transfer function, travelling salesman problem, wave

Michael Bronstein

Professor, Chair in Machine Learning and Pattern Recognition at Imperial College London

atlas experiment, autoencoder, backpropagation, basis (linear algebra), community structure, computational complexity theory, convolution, curvature, deep learning, density functional theory, euclidean space, fiber bundle, fourier transform, laplace operator, linear algebra, linear combination, matching (graph theory), matrix (mathematics), matrix completion, quantum mechanics, spectral density, tangent bundle, transfer function, travelling salesman problem, wave

Xavier Bresson

Assoc Professor of Computer Science (Data Science and AI) at Nanyang Technological University

Yann LeCun

Director at Facebook AI Research

applied and computational geometry, applied mathematics, argument, artificial neural network, asthma, atlas experiment, autoencoder, automation, backpropagation, basis (linear algebra), bit, breast cancer, cancer, cartesian coordinate system, causal model, causality, chain rule, clinical trial, code, community structure, computational complexity theory, computer vision, concept, conference on neural information processing systems, consciousness, convolution, courant institute of mathematical sciences, creativity, curvature, data center, data science, deep learning, deepmind, density functional theory, economics, education, educational technology, equation, euclidean space, executive functions, experiment, explanation, facial recognition system, fiber bundle, fourier transform, function (mathematics), geoffrey hinton, google translate, h-index, idea, image segmentation, invention, laplace operator, likelihood function, linear algebra, linear combination, machine learning, mammography, matching (graph theory), math, mathematical optimization, matrix (mathematics), matrix completion, matrix multiplication, medical imaging, mind, motivation, natural language processing, perception, perceptron, prediction, problem solving, pytorch, quantum mechanics, radiology, randomized controlled trial, reason, reinforcement learning, risk, robot, robotics, science, self-driving car, sensitivity analysis, simulation and modeling, spectral density, speech recognition, stochastic gradient descent, surgery, tangent bundle, theory, thermodynamic free energy, transfer function, travelling salesman problem, trial and error, understanding, watson (computer), wave, wire-frame model, yoshua bengio, yt:cc=on

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