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Career

· Research Scientist, DeepMind2013–
· Postdoctoral researcher, Gatsby2013–
· PhD Student in Machine Learning Group, University of Toronto2013–

Publications (45)

Probabilistic Matrix Factorization
Neural Information Processing Systems · 2007
4,746
cited
The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables
International Conference on Learning Representations · 2016
2,729
cited
Restricted Boltzmann machines for collaborative filtering
International Conference on Machine Learning · 2007
2,076
cited
Bayesian probabilistic matrix factorization using Markov chain Monte Carlo
International Conference on Machine Learning · 2008
1,535
cited
Disentangling by Factorising
International Conference on Machine Learning · 2018
1,467
cited
A Scalable Hierarchical Distributed Language Model
Neural Information Processing Systems · 2008
1,020
cited
Neural Variational Inference and Learning in Belief Networks
International Conference on Machine Learning · 2014
728
cited
Three new graphical models for statistical language modelling
International Conference on Machine Learning · 2007
653
cited
Learning word embeddings efficiently with noise-contrastive estimation
Neural Information Processing Systems · 2013
630
cited
A fast and simple algorithm for training neural probabilistic language models
International Conference on Machine Learning · 2012
586
cited
Attentive Neural Processes
International Conference on Learning Representations · 2019
493
cited
Monte Carlo Gradient Estimation in Machine Learning
Journal of machine learning research · 2019
474
cited
Deep AutoRegressive Networks
International Conference on Machine Learning · 2013
300
cited
Variational Inference for Monte Carlo Objectives
International Conference on Machine Learning · 2016
298
cited
REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models
Neural Information Processing Systems · 2017
291
cited
Implicit Reparameterization Gradients
Neural Information Processing Systems · 2018
247
cited
Filtering Variational Objectives
Neural Information Processing Systems · 2017
218
cited
The Lipschitz Constant of Self-Attention
International Conference on Machine Learning · 2020
187
cited
MuProp: Unbiased Backpropagation for Stochastic Neural Networks
International Conference on Learning Representations · 2015
145
cited
Resampled Priors for Variational Autoencoders
International Conference on Artificial Intelligence and Statistics · 2018
118
cited
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Andriy Mnih | Researcher Profile | Sotabase | Sotabase