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Score Modeling for Simulation-based Inference


Sep 28, 2022
Tomas Geffner, George Papamakarios, Andriy Mnih

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Unbiased Gradient Estimation with Balanced Assignments for Mixtures of Experts


Sep 24, 2021
Wouter Kool, Chris J. Maddison, Andriy Mnih

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Coupled Gradient Estimators for Discrete Latent Variables


Jun 15, 2021
Zhe Dong, Andriy Mnih, George Tucker

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* Under Review 

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Generalized Doubly Reparameterized Gradient Estimators


Jan 26, 2021
Matthias Bauer, Andriy Mnih

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DisARM: An Antithetic Gradient Estimator for Binary Latent Variables


Jun 18, 2020
Zhe Dong, Andriy Mnih, George Tucker

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The Lipschitz Constant of Self-Attention


Jun 08, 2020
Hyunjik Kim, George Papamakarios, Andriy Mnih

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Q-Learning in enormous action spaces via amortized approximate maximization


Jan 22, 2020
Tom Van de Wiele, David Warde-Farley, Andriy Mnih, Volodymyr Mnih

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* A previous version of this work appeared at the Deep Reinforcement Learning Workshop, NeurIPS 2018 

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Sparse Orthogonal Variational Inference for Gaussian Processes


Oct 24, 2019
Jiaxin Shi, Michalis K. Titsias, Andriy Mnih

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Monte Carlo Gradient Estimation in Machine Learning


Jun 25, 2019
Shakir Mohamed, Mihaela Rosca, Michael Figurnov, Andriy Mnih

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* 59 pages, under review 

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Attentive Neural Processes


Jan 17, 2019
Hyunjik Kim, Andriy Mnih, Jonathan Schwarz, Marta Garnelo, Ali Eslami, Dan Rosenbaum, Oriol Vinyals, Yee Whye Teh

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