Andriy Mnih
Andriy Mnih
Research Scientist at DeepMind
Email verificata su cs.toronto.edu - Home page
Titolo
Citata da
Citata da
Anno
Probabilistic matrix factorization
R Salakhutdinov, A Mnih
Advances in neural information processing systems 20, 1257-1264, 2008
3739*2008
Restricted Boltzmann machines for collaborative filtering
R Salakhutdinov, A Mnih, G Hinton
Proceedings of the 24th international conference on Machine learning, 791-798, 2007
18932007
Bayesian probabilistic matrix factorization using Markov chain Monte Carlo
R Salakhutdinov, A Mnih
Proceedings of the 25th international conference on Machine learning, 880-887, 2008
14372008
Bayesian probabilistic matrix factorization using Markov chain Monte Carlo
R Salakhutdinov, A Mnih
Proceedings of the 25th international conference on Machine learning, 880-887, 2008
14272008
A scalable hierarchical distributed language model
A Mnih, GE Hinton
Advances in Neural Information Processing Systems 21, 1081-1088, 2009
10532009
The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables
CJ Maddison, A Mnih, YW Teh
International Conference on Learning Representations 2017, 2016
10382016
Three new graphical models for statistical language modelling
A Mnih, G Hinton
Proceedings of the 24th international conference on Machine learning, 641-648, 2007
6692007
Neural Variational Inference and Learning in Belief Networks
A Mnih, K Gregor
International Conference on Machine Learning 2014, 2014
5832014
Learning word embeddings efficiently with noise-contrastive estimation
A Mnih, K Kavukcuoglu
Advances in Neural Information Processing Systems, 2265-2273, 2013
5212013
A fast and simple algorithm for training neural probabilistic language models
A Mnih, YW Teh
International Conference on Machine Learning 2012, 2012
5132012
Disentangling by factorising
H Kim, A Mnih
International Conference on Machine Learning 2018, 2018
3972018
Deep autoregressive networks
K Gregor, I Danihelka, A Mnih, C Blundell, D Wierstra
Proceedings of the 31st International Conference on Machine Learning (ICML…, 2014
2152014
Variational inference for Monte Carlo objectives
A Mnih, DJ Rezende
International Conference on Machine Learning 2016, 2016
2002016
REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models
G Tucker, A Mnih, CJ Maddison, J Lawson, J Sohl-Dickstein
Advances in Neural Information Processing Systems, 2624-2633, 2017
1872017
MuProp: Unbiased Backpropagation for Stochastic Neural Networks
S Gu, S Levine, I Sutskever, A Mnih
International Conference on Learning Representations 2016, 2015
1102015
Filtering Variational Objectives
CJ Maddison, D Lawson, G Tucker, N Heess, M Norouzi, A Mnih, ...
Advances in Neural Information Processing Systems 2017, 2017
1062017
Implicit reparameterization gradients
M Figurnov, S Mohamed, A Mnih
Advances in Neural Information Processing Systems, 441-452, 2018
1012018
Visualizing similarity data with a mixture of maps
J Cook, I Sutskever, A Mnih, G Hinton
Artificial Intelligence and Statistics, 67-74, 2007
972007
Attentive Neural Processes
H Kim, A Mnih, J Schwarz, M Garnelo, A Eslami, D Rosenbaum, O Vinyals, ...
International Conference on Learning Representations 2019, 2018
812018
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
602020
Il sistema al momento non pu eseguire l'operazione. Riprova pi tardi.
Articoli 1–20