Dmitry Vetrov
37 papers · 2010–2026 · 12 conferences · across top CS/AI conferences
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Conferences
ICML (8)
AISTATS (5)
AAAI (4)
CVPR (3)
ICLR (3)
NIPS (3)
ACL (2)
ACML (2)
ICCV (2)
INTERSPEECH (2)
UAI (2)
EMNLP (1)
Top co-authors
Keywords
variational inference
(5)
model compression
(4)
image classification
(4)
bayesian inference
(4)
neural network
(3)
generative model
(3)
diffusion model
(3)
variational autoencoder
(2)
latent variable
(2)
language model
(2)
image generation
(2)
bayesian nonparametrics
(2)
recurrent neural network
(2)
few-shot learning
(2)
posterior approximation
(2)
language modeling
(2)
neural network compression
(2)
tensor decomposition
(2)
text generation
(2)
automatic relevance determination
(2)
Papers
Streaming Generation of Co-Speech Gestures via Accelerated Rolling Diffusion
AAAI 2026
Diffusion on Language Model Encodings for Protein Sequence Generation
ICML 2025
TEncDM: Understanding the Properties of the Diffusion Model in the Space of Language Model Encodings
AAAI 2025
SDE Matching: Scalable and Simulation-Free Training of Latent Stochastic Differential Equations
ICML 2025
HairFastGAN: Realistic and Robust Hair Transfer with a Fast Encoder-Based Approach
NIPS 2024
Where Do Large Learning Rates Lead Us?
NIPS 2024
Neural Flow Diffusion Models: Learnable Forward Process for Improved Diffusion Modelling
NIPS 2024
The Devil is in the Details: StyleFeatureEditor for Detail-Rich StyleGAN Inversion and High Quality Image Editing
CVPR 2024
Neural Diffusion Models
ICML 2024
MARS: Masked Automatic Ranks Selection in Tensor Decompositions
AISTATS 2023
UnDiff: Unsupervised Voice Restoration with Unconditional Diffusion Model
INTERSPEECH 2023
StyleDomain: Efficient and Lightweight Parameterizations of StyleGAN for One-shot and Few-shot Domain Adaptation
ICCV 2023
FFC-SE: Fast Fourier Convolution for Speech Enhancement
INTERSPEECH 2022
Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation
UAI 2020
Low-Variance Black-Box Gradient Estimates for the Plackett-Luce Distribution
AAAI 2020
Involutive MCMC: a Unifying Framework
ICML 2020
Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics
ICML 2020
Deterministic Decoding for Discrete Data in Variational Autoencoders
AISTATS 2020
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning
ICLR 2020
Structured Sparsification of Gated Recurrent Neural Networks
AAAI 2020
Doubly Semi-Implicit Variational Inference
AISTATS 2019
Variational Autoencoder with Arbitrary Conditioning
ICLR 2019
Variance Networks: When Expectation Does Not Meet Your Expectations
ICLR 2019
Efficient Language Modeling with Automatic Relevance Determination in Recurrent Neural Networks
ACL 2019
Subspace Inference for Bayesian Deep Learning
UAI 2019
ReSet: Learning Recurrent Dynamic Routing in ResNet-like Neural Networks
ACML 2018
Few-shot Generative Modelling with Generative Matching Networks
AISTATS 2018
Bayesian Compression for Natural Language Processing
EMNLP 2018
Conditional Generators of Words Definitions
ACL 2018
Variational Dropout Sparsifies Deep Neural Networks
ICML 2017
Spatially Adaptive Computation Time for Residual Networks
CVPR 2017
Breaking Sticks and Ambiguities with Adaptive Skip-gram
AISTATS 2016
Inferring M-Best Diverse Labelings in a Single One
ICCV 2015
Putting MRFs on a Tensor Train
ICML 2014
Variational Inference for Sequential Distance Dependent Chinese Restaurant Process
ICML 2014
Spatial Inference Machines
CVPR 2013
Variational Relevance Vector Machine for Tabular Data
ACML 2010