Shakir Mohamed

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Balaji LakshminarayananSenior Staff Research Scientist at Google DeepMindAdresse e-mail validée de google.com
Mihaela RoscaDeepmindAdresse e-mail validée de google.com
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleAdresse e-mail validée de eng.cam.ac.uk
Tshilidzi Marwala (チリツィマルワラ)Rector of the United Nations UniversityAdresse e-mail validée de unu.edu
Katherine HellerGoogle ResearchAdresse e-mail validée de gatsby.ucl.ac.uk
Diederik P. KingmaAnthropicAdresse e-mail validée de anthropic.com
Max WellingCAIO CuspAI & Professor Machine Learning, University of AmsterdamAdresse e-mail validée de uva.nl
Ivo DanihelkaDeepMindAdresse e-mail validée de google.com
Nando de FreitasCIFAR & DeepMindAdresse e-mail validée de google.com
Mohammad Emtiyaz KhanCenter for Advanced Intelligence Project (AIP), RIKEN, TokyoAdresse e-mail validée de postman.riken.jp
Marc DeisenrothUniversity College London and Google DeepMindAdresse e-mail validée de ucl.ac.uk
Fulufhelo NelwamondoPrincipal researcher, CSIR/ Visiting Professor of Electrical Engineering, University of JohannesburgAdresse e-mail validée de uj.ac.za
Kevin MurphyResearch Scientist, GoogleAdresse e-mail validée de google.com
Ziyu WangDeepmindAdresse e-mail validée de google.com
Benjamin M. MarlinManning College of Information and Computer Sciences, UMass AmherstAdresse e-mail validée de umass.edu
David A. KnowlesColumbia University & New York Genome CenterAdresse e-mail validée de columbia.edu
Finale Doshi-VelezProfessor, HarvardAdresse e-mail validée de seas.harvard.edu
Mikkel N. SchmidtTechnical University of DenmarkAdresse e-mail validée de dtu.dk

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Shakir Mohamed

Research Director, Google DeepMind

Adresse e-mail validée de deepmind.com - Page d'accueil

Machine Learning Bayesian Statistics Deep Learning Sociotechnical AI Artificial Intelligence


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Stochastic Backpropagation and Approximate Inference in Deep Generative Models DJ Rezende, S Mohamed, D Wierstra The 31st International Conference on Machine Learning (ICML), 2014	6300	2014
beta-vae: Learning basic visual concepts with a constrained variational framework. I Higgins, L Matthey, A Pal, CP Burgess, X Glorot, MM Botvinick, ... ICLR (Poster) 3, 2017	5742	2017
Variational inference with normalizing flows D Rezende, S Mohamed International conference on machine learning, 1530-1538, 2015	4864	2015
Semi-supervised learning with deep generative models DP Kingma, S Mohamed, D Jimenez Rezende, M Welling Advances in neural information processing systems 27, 2014	3805	2014
Normalizing flows for probabilistic modeling and inference G Papamakarios, E Nalisnick, DJ Rezende, S Mohamed, ... Journal of Machine Learning Research 22 (57), 1-64, 2021	1932	2021
A clinically applicable approach to continuous prediction of future acute kidney injury N Tomašev, X Glorot, JW Rae, M Zielinski, H Askham, A Saraiva, ... Nature 572 (7767), 116-119, 2019	968	2019
Skilful precipitation nowcasting using deep generative models of radar S Ravuri, K Lenc, M Willson, D Kangin, R Lam, P Mirowski, M Fitzsimons, ... Nature 597 (7878), 672-677, 2021	875	2021
Decolonial AI: Decolonial theory as sociotechnical foresight in artificial intelligence S Mohamed, MT Png, W Isaac Philosophy & Technology 33, 659-684, 2020	577	2020
Learning skillful medium-range global weather forecasting R Lam, A Sanchez-Gonzalez, M Willson, P Wirnsberger, M Fortunato, ... Science 382 (6677), 1416-1421, 2023	572	2023
Monte carlo gradient estimation in machine learning S Mohamed, M Rosca, M Figurnov, A Mnih Journal of Machine Learning Research 21 (132), 1-62, 2020	525	2020
Learning in implicit generative models S Mohamed, B Lakshminarayanan arXiv preprint arXiv:1610.03483, 2016	507	2016
Variational information maximisation for intrinsically motivated reinforcement learning S Mohamed, D Jimenez Rezende Advances in neural information processing systems 28, 2015	481	2015
Unsupervised learning of 3d structure from images D Jimenez Rezende, SM Eslami, S Mohamed, P Battaglia, M Jaderberg, ... Advances in neural information processing systems 29, 2016	466	2016
The cramer distance as a solution to biased wasserstein gradients MG Bellemare, I Danihelka, W Dabney, S Mohamed, ... arXiv preprint arXiv:1705.10743, 2017	441	2017
Variational approaches for auto-encoding generative adversarial networks M Rosca, B Lakshminarayanan, D Warde-Farley, S Mohamed arXiv preprint arXiv:1706.04987, 2017	336	2017
One-shot generalization in deep generative models D Rezende, S Mohamed, I Danihelka, K Gregor, D Wierstra International Conference on Machine Learning, 1521-1529, 2016	319	2016
AI for social good: unlocking the opportunity for positive impact N Tomašev, J Cornebise, F Hutter, S Mohamed, A Picciariello, B Connelly, ... Nature Communications 11 (1), 2468, 2020	305	2020
GraphCast: Learning skillful medium-range global weather forecasting R Lam, A Sanchez-Gonzalez, M Willson, P Wirnsberger, M Fortunato, ... arXiv preprint arXiv:2212.12794, 2022	298	2022
Implicit reparameterization gradients M Figurnov, S Mohamed, A Mnih Advances in neural information processing systems 31, 2018	296	2018
Many paths to equilibrium: GANs do not need to decrease a divergence at every step W Fedus, M Rosca, B Lakshminarayanan, AM Dai, S Mohamed, ... arXiv preprint arXiv:1710.08446, 2017	271	2017

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