Publications (27)
MuProp: Unbiased Backpropagation for Stochastic Neural Networks
Shixiang Gu, Sergey Levine, Ilya Sutskever +1
Variational inference for Monte Carlo objectives
Andriy Mnih, Danilo J. Rezende
Particle Value Functions
Chris J. Maddison, Dieterich Lawson, George Tucker +4
The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables
Chris J. Maddison, Andriy Mnih, Yee Whye Teh
Deep AutoRegressive Networks
Karol Gregor, Ivo Danihelka, Andriy Mnih +2
Uncertainty evaluation of segmentation models for Earth observation
Melanie Rey, Andriy Mnih, Maxim Neumann +2
Generalized Doubly Reparameterized Gradient Estimators
Matthias Bauer, Andriy Mnih
The Lipschitz Constant of Self-Attention
Hyunjik Kim, George Papamakarios, Andriy Mnih
Monte Carlo Gradient Estimation in Machine Learning
Shakir Mohamed, Mihaela Rosca, Michael Figurnov +1
Neural Variational Inference and Learning in Belief Networks
Andriy Mnih, Karol Gregor
Variational Memory Addressing in Generative Models
Jörg Bornschein, Andriy Mnih, Daniel Zoran +1
REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models
George Tucker, Andriy Mnih, Chris J. Maddison +2
Q-Learning in enormous action spaces via amortized approximate maximization
Tom Van de Wiele, David Warde-Farley, Andriy Mnih +1
Learning Item Trees for Probabilistic Modelling of Implicit Feedback
Andriy Mnih, Yee Whye Teh
Coupled Gradient Estimators for Discrete Latent Variables
Zhe Dong, Andriy Mnih, George Tucker
Introduction to Stochastic Differential Equations for Generative Machine Learning: A Variational Perspective
Ole Winther, Paul Jeha, Sander Dieleman +3
Sparse Orthogonal Variational Inference for Gaussian Processes
Jiaxin Shi, Michalis K. Titsias, Andriy Mnih
Implicit Reparameterization Gradients
Michael Figurnov, Shakir Mohamed, Andriy Mnih
Filtering Variational Objectives
Chris J. Maddison, Dieterich Lawson, George Tucker +5
A Fast and Simple Algorithm for Training Neural Probabilistic Language Models
Andriy Mnih, Yee Whye Teh
Compositional Score Modeling for Simulation-based Inference
Tomas Geffner, George Papamakarios, Andriy Mnih
Disentangling by Factorising
Hyunjik Kim, Andriy Mnih
Resampled Priors for Variational Autoencoders
Matthias Bauer, Andriy Mnih
Attentive Neural Processes
Hyunjik Kim, Andriy Mnih, Jonathan Schwarz +5
Schrödinger Bridge Flow for Unpaired Data Translation
Valentin De Bortoli, Iryna Korshunova, Andriy Mnih +1
Unbiased Gradient Estimation with Balanced Assignments for Mixtures of Experts
Wouter Kool, Chris J. Maddison, Andriy Mnih
DisARM: An Antithetic Gradient Estimator for Binary Latent Variables
Zhe Dong, Andriy Mnih, George Tucker