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← Authors

Andriy Mnih

22 papers · 2007–2024 · 5 conferences · across top CS/AI conferences

Achievements

Jump to papers ↓
+11 more ↓ 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🌈 Renaissance Researcher (5) πŸ—ΊοΈ Taxonomy Completionist (18) 🐣 Hot Topic Early Bird
πŸ—ΊοΈ Taxonomy Completionist (18) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (3) 🌱 Topic Pioneer 🧬 Topic Evolution πŸ† Keyword Champion πŸ”₯ Unstoppable (6) πŸ’Ž Century Club (22) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (106)

Conferences

NIPS (11) ICML (7) AISTATS (2) ICLR (1) JMLR (1)

Top co-authors

George Tucker (4) Hyunjik Kim (3) Zhe Dong (2) Shakir Mohamed (2) John Lawson (2) Karol Gregor (2) Matthias Bauer (2) Chris J Maddison (2) Arnaud Doucet (2) George Papamakarios (2)

Research topics

Optimization & Theory (1)

Keywords

variational inference (11) generative model (8) gradient estimator (5) variance reduction (5) variational autoencoder (4) latent variable model (3) language modeling (3) representation learning (3) reparameterization trick (2) neural network (2) collaborative filtering (2) importance sampling (2) discrete latent variable (2) probabilistic model (2) hierarchical model (2) recommender system (2) deep learning (1) semantic representation (1) optimal transport (1) few-shot learning (1)

Papers

Schrodinger Bridge Flow for Unpaired Data Translation NIPS 2024 Compositional Score Modeling for Simulation-Based Inference ICML 2023 Generalized Doubly Reparameterized Gradient Estimators ICML 2021 Coupled Gradient Estimators for Discrete Latent Variables NIPS 2021 The Lipschitz Constant of Self-Attention ICML 2021 Sparse Orthogonal Variational Inference for Gaussian Processes AISTATS 2020 Monte Carlo Gradient Estimation in Machine Learning JMLR 2020 DisARM: An Antithetic Gradient Estimator for Binary Latent Variables NIPS 2020 Resampled Priors for Variational Autoencoders AISTATS 2019 Attentive Neural Processes ICLR 2019 Implicit Reparameterization Gradients NIPS 2018 Disentangling by Factorising ICML 2018 Filtering Variational Objectives NIPS 2017 REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models NIPS 2017 Variational Memory Addressing in Generative Models NIPS 2017 Variational Inference for Monte Carlo Objectives ICML 2016 Deep AutoRegressive Networks ICML 2014 Neural Variational Inference and Learning in Belief Networks ICML 2014 Learning word embeddings efficiently with noise-contrastive estimation NIPS 2013 Learning Label Trees for Probabilistic Modelling of Implicit Feedback NIPS 2012 A Scalable Hierarchical Distributed Language Model NIPS 2008 Probabilistic Matrix Factorization NIPS 2007