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Show (46)

Weiqiang Wen

Cryptanalyst

absolute value, algebraic number field, algebraic number theory, algorithm, basis (linear algebra), condition number, curve, embedding, field (mathematics), function (mathematics), geometry, lattice (group), linear combination, linear independence, logarithm, modular arithmetic, number, number theory, polynomial, quantity, random walk, rational number, ring (mathematics), time complexity, vector space

Alexey Gorshkov

Physicist at NIST

algorithm, behavior, coefficient, computer, energy, function (mathematics), gradient descent, ground state, hamiltonian (quantum mechanics), indoor cycling, linear combination, mathematical optimization, maximum cut, oak, optimization problem, paper, quantum computing, quantum supremacy, reason, simulation, space, spin (physics), triangle, truth, weight

Matthew Wicker

Doctoral Candidate at University of Oxford

artificial neural network, bit, collision avoidance (spacecraft), collision avoidance system, determinism, dimension, function (mathematics), future, interval (mathematics), linear combination, monte carlo method, probability, probability distribution, rapid transit, reason, regression analysis, sensitivity analysis, space, uncertainty, unmanned aerial vehicle, vienna, weight

Yijia Wang

Analyst at Parsons School of Design

ads recommendation, advertising, algorithm, application software, attention, bit, censorship, china, christianity, click-through rate, common technologies for feed and ads recommendation, computer, computer data storage, computer network, cosine similarity, decentralised system, encryption, equation, feed recommendation , finite set, freedom of the press, function (mathematics), image understanding, infrastructure, introduction - feed, ads, search and spam, javascript, letter case, linear combination, logic, mixture model, multimedia, multimedia infrastructure, multimedia search, multivariate random variable, nicotine, online and offline, prediction, risk, safeway inc., scraper (archaeology), simulation, social media, softmax function, software , source lines of code, speech recognition, summation, telegram (software), tool, trust (social science), url, video, video representations used in production, video search engine, video understanding, virtual private network

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

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

Tengfei Ma

Research Staff Member at IBM T.J. Watson Research Center

activation function, artificial intelligence, artificial neural network, association for computing machinery, autoencoder, basis (linear algebra), cluster analysis, computer science 2020, computer science event 2020, computer vision, convolutional neural network, cross entropy, data science, deep learning, domain-specific language, eigenvalues and eigenvectors, euclidean vector, fourier transform, k-nearest neighbors algorithm, kdd2020, linear combination, low-pass filter, machine learning, matrix (mathematics), parameter, semi-supervised learning, shortest path problem, statistical classification, unsupervised learning, vector space, vertex (graph theory), voicemail

Lingfei (Teddy) Wu

Principal Scientist at Principal Scientist

activation function, artificial intelligence, artificial neural network, association for computing machinery, autoencoder, basis (linear algebra), cluster analysis, computer science 2020, computer science event 2020, computer vision, convolutional neural network, cross entropy, data science, deep learning, domain-specific language, eigenvalues and eigenvectors, euclidean vector, fourier transform, k-nearest neighbors algorithm, kdd2020, linear combination, low-pass filter, machine learning, matrix (mathematics), parameter, semi-supervised learning, shortest path problem, statistical classification, unsupervised learning, vector space, vertex (graph theory), voicemail

Tyler Derr

Vanderbilt University at Assistant Professor

activation function, artificial intelligence, artificial neural network, association for computing machinery, autoencoder, basis (linear algebra), cluster analysis, computer science 2020, computer science event 2020, computer vision, convolutional neural network, cross entropy, data science, deep learning, domain-specific language, eigenvalues and eigenvectors, euclidean vector, fourier transform, k-nearest neighbors algorithm, kdd2020, linear combination, low-pass filter, machine learning, matrix (mathematics), parameter, semi-supervised learning, shortest path problem, statistical classification, unsupervised learning, vector space, vertex (graph theory), voicemail

Yiqi Wang

PhD Student at Michigan State University

Yao Ma

Graduate Research Assistant at Michigan State University

Hong Chen

Professor at The Chinese University of Hong Kong

Wenbing Huang

Ph.D. Candidate at Tsinghua University

Tingyang Xu

Graduate Assistant at University of Connecticut

Dmitry Khovratovic

Ethereum Foundation at Cryptography Researcher

#realworldcrypto, 64-bit computing, algorithm, bit, block cipher mode of operation, complexity, computer, cryptanalysis, cryptocurrency, curve, differential cryptanalysis, equation, exponentiation, force, function (mathematics), hash function, integer, linear combination, number, permutation, planet, prime number, reason, rsa (cryptosystem), star, truth

Nigel Smart

Professor at COSIC (KU Leuven)

#realworldcrypto, 64-bit computing, algorithm, api, array data structure, bit, block cipher mode of operation, communication protocol, compiler, complexity, computer, computer programming, conditional (computer programming), cryptanalysis, cryptocurrency, curve, data type, differential cryptanalysis, domain-specific language, equation, exponentiation, force, fraud, function (mathematics), functional programming, hash function, imperative programming, integer, key management, linear combination, number, openssl, permutation, planet, prime number, program optimization, programming language, prototype, public-key cryptography, reason, research, reserved word, rsa (cryptosystem), runtime system, software repository, star, statistics, system, truth, usability

Michael Riabzev

Co-Founder & Chief-Architect at StarkWare

algebra, argument, central processing unit, cloud computing, coefficient, communication protocol, computer, crypto 2020, crypto development, crypto development 2020, crypto events 2020, crypto strategy 2020, crypto trading, cryptocurrency development, equation, eth conference, ethereum 2020 , ethereum hackathon, ethglobal, function (mathematics), intel, interpolation, language, linear combination, mathematical proof, michael riabzev, motivation, number, perspectives of ethereum, polynomial, proof of knowledge, reason, scalability, science, square root, stark proof system, tokens, tokens 2020, troubleshooting, witness, zero of a function

Vladyslav Usenko

Machine Learning Engineer at Apple

3d rotation group, acceleration, attention, automatic differentiation, complexity, computer hardware, computer vision, derivative, distance, jacobian matrix and determinant, linear combination, map, mathematical optimization, matrix (mathematics), multiplication, reason, recursion, recursion (computer science), rotation (mathematics), space, speed, spline (mathematics), time, vector space

Christiane Sommer

Assistant Professor at National Institutes for Natural Sciences

3d rotation group, acceleration, attention, automatic differentiation, complexity, computer hardware, computer vision, derivative, distance, jacobian matrix and determinant, linear combination, map, mathematical optimization, matrix (mathematics), multiplication, reason, recursion, recursion (computer science), rotation (mathematics), space, speed, spline (mathematics), time, vector space

Nikolaus Demmel

PHD Student at Technical University Munich

3d rotation group, acceleration, attention, automatic differentiation, complexity, computer hardware, computer vision, derivative, distance, jacobian matrix and determinant, linear combination, map, mathematical optimization, matrix (mathematics), multiplication, reason, recursion, recursion (computer science), rotation (mathematics), space, speed, spline (mathematics), time, vector space

Daniel Cremers

Director and co-Founder at Artisense

3d rotation group, ablation, acceleration, apple inc., artificial neural network, attention, automatic differentiation, calculator, camera, car, certainty, complexity, computer hardware, computer vision, concept, cost, covid-19 pandemic, deep learning, derivative, distance, evaluation, image, jacobian matrix and determinant, learning, lighting, linear combination, map, mathematical optimization, matrix (mathematics), motor trend, multiplication, odometer, paper, photography, postnet, predation, reason, recursion, recursion (computer science), rock music, rotation (mathematics), space, speed, spline (mathematics), time, tree, turkey, vector space, york

Heather Harrington

Professor of Mathematics at University of Oxford

applied and computational geometry, applied mathematics, artificial neural network, carbon, cartesian coordinate system, continuous function, curvature, data science, directional derivative, ecology, equation, experiment, function (mathematics), gradient, gradient descent, graph (discrete mathematics), homology (mathematics), hubble space telescope, instagram, linear combination, manifold, math, mathematics, numerical analysis, polynomial, sequence, simulation and modeling, statistics, variance, vertex (graph theory)

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