Andriy Mnih
22 papers · 2007–2024 · 5 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+11 more ↓ Show less ↑
π§ Keyword Pioneer π Interdisciplinary Bridge π Renaissance Researcher (5) πΊοΈ Taxonomy Completionist (18) π£ Hot Topic Early Bird
πΊοΈ
Taxonomy Completionist
(18)
π
Interdisciplinary Bridge
π§
Keyword Pioneer
π
Keyword Trendsetter Combo
(3)
π±
Topic Pioneer
π§¬
Topic Evolution
π
Keyword Champion
π₯
Unstoppable
(6)
π
Century Club
(22)
π
Trend Setter
ποΈ
Keyword Collector
(106)
Conferences
NIPS (11)
ICML (7)
AISTATS (2)
ICLR (1)
JMLR (1)
Top co-authors
Research topics
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