Dmitry P. Vetrov

Christian A. Naesseth

CoRR, 2023

UnDiff: Unsupervised Voice Restoration with Unconditional Diffusion Model.

[BibT_eX]

[DOI]

Anastasiia Iashchenko

CoRR, 2023

Differentiable Rendering with Reparameterized Volume Sampling.

[BibT_eX]

[DOI]

CoRR, 2023

Star-Shaped Denoising Diffusion Probabilistic Models.

[BibT_eX]

[DOI]

CoRR, 2023

To Stay or Not to Stay in the Pre-train Basin: Insights on Ensembling in Transfer Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Star-Shaped Denoising Diffusion Probabilistic Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Entropic Neural Optimal Transport via Diffusion Processes.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

StyleDomain: Efficient and Lightweight Parameterizations of StyleGAN for One-shot and Few-shot Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

HIFI++: A Unified Framework for Bandwidth Extension and Speech Enhancement.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2023

MARS: Masked Automatic Ranks Selection in Tensor Decompositions.

[BibT_eX]

[DOI]

Maxim Kodryan

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

StyleDomain: Analysis of StyleSpace for Domain Adaptation of StyleGAN.

[BibT_eX]

[DOI]

CoRR, 2022

HiFi++: a Unified Framework for Neural Vocoding, Bandwidth Extension and Speech Enhancement.

[BibT_eX]

[DOI]

CoRR, 2022

Training Scale-Invariant Neural Networks on the Sphere Can Happen in Three Regimes.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

HyperDomainNet: Universal Domain Adaptation for Generative Adversarial Networks.

[BibT_eX]

[DOI]

Aibek Alanov

Vadim Titov

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

FFC-SE: Fast Fourier Convolution for Speech Enhancement.

[BibT_eX]

[DOI]

Proceedings of the Interspeech 2022, 2022

2021

Machine Learning Methods for Spectral Efficiency Prediction in Massive MIMO Systems.

[BibT_eX]

[DOI]

CoRR, 2021

Automating Control of Overestimation Bias for Continuous Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2021

Quantization of Generative Adversarial Networks for Efficient Inference: a Methodological Study.

[BibT_eX]

[DOI]

Pavel Andreev

Alexander Fritzler

CoRR, 2021

Mean Embeddings with Test-Time Data Augmentation for Ensembling of Representations.

[BibT_eX]

[DOI]

Arsenii Ashukha

Andrei Atanov

CoRR, 2021

Towards Practical Credit Assignment for Deep Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2021

Leveraging Recursive Gumbel-Max Trick for Approximate Inference in Combinatorial Spaces.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On the Periodic Behavior of Neural Network Training with Batch Normalization and Weight Decay.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Reintroducing Straight-Through Estimators as Principled Methods for Stochastic Binary Networks.

[BibT_eX]

[DOI]

Viktor Yanush

Alexander Shekhovtsov

Dmitry Molchanov

CoRR, 2020

Deep Ensembles on a Fixed Memory Budget: One Wide Network or Several Thinner Ones?

[BibT_eX]

[DOI]

CoRR, 2020

Stochasticity in Neural ODEs: An Empirical Study.

[BibT_eX]

[DOI]

Viktor Oganesyan

Alexandra Volokhova

CoRR, 2020

User-controllable Multi-texture Synthesis with Generative Adversarial Networks.

[BibT_eX]

[DOI]

Proceedings of the 15th International Joint Conference on Computer Vision, 2020

Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

On Power Laws in Deep Ensembles.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Involutive MCMC: a Unifying Framework.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Deterministic Decoding for Discrete Data in Variational Autoencoders.

[BibT_eX]

[DOI]

Daniil Polykovskiy

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Structured Sparsification of Gated Recurrent Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Low-Variance Black-Box Gradient Estimates for the Plackett-Luce Distribution.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

MLRG Deep Curvature.

[BibT_eX]

[DOI]

CoRR, 2019

Semi-Conditional Normalizing Flows for Semi-Supervised Learning.

[BibT_eX]

[DOI]

CoRR, 2019

Subspace Inference for Bayesian Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Efficient Language Modeling with Automatic Relevance Determination in Recurrent Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 4th Workshop on Representation Learning for NLP, 2019

Importance Weighted Hierarchical Variational Inference.

[BibT_eX]

[DOI]

Artem Sobolev

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

The Implicit Metropolis-Hastings Algorithm.

[BibT_eX]

[DOI]

Kirill Neklyudov

Evgenii Egorov

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Simple Baseline for Bayesian Uncertainty in Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Prior of a Googol Gaussians: a Tensor Ring Induced Prior for Generative Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Uncertainty Estimation via Stochastic Batch Normalization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Networks - ISNN 2019, 2019

Variance Networks: When Expectation Does Not Meet Your Expectations.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

Variational Autoencoder with Arbitrary Conditioning.

[BibT_eX]

[DOI]

Oleg Ivanov

Proceedings of the 7th International Conference on Learning Representations, 2019

The Deep Weight Prior.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

Doubly Semi-Implicit Variational Inference.

[BibT_eX]

[DOI]

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

A Simple Method to Evaluate Support Size and Non-uniformity of a Decoder-Based Generative Model.

[BibT_eX]

[DOI]

Kirill Struminsky

Proceedings of the Analysis of Images, Social Networks and Texts, 2019

2018

Bayesian Sparsification of Gated Recurrent Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2018

Variational Dropout via Empirical Bayes.

[BibT_eX]

[DOI]

Valery Kharitonov

Dmitry Molchanov

CoRR, 2018

Metropolis-Hastings view on variational inference and adversarial training.

[BibT_eX]

[DOI]

Kirill Neklyudov

Pavel Shvechikov

CoRR, 2018

The Deep Weight Prior. Modeling a prior distribution for CNNs using generative models.

[BibT_eX]

[DOI]

CoRR, 2018

Pairwise Augmented GANs with Adversarial Reconstruction Loss.

[BibT_eX]

[DOI]

CoRR, 2018

Universal Conditional Machine.

[BibT_eX]

[DOI]

Oleg Ivanov

CoRR, 2018

Averaging Weights Leads to Wider Optima and Better Generalization.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Bayesian Incremental Learning for Deep Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

Bayesian Compression for Natural Language Processing.

[BibT_eX]

[DOI]

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Few-shot Generative Modelling with Generative Matching Networks.

[BibT_eX]

[DOI]

Sergey Bartunov

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

ReSet: Learning Recurrent Dynamic Routing in ResNet-like Neural Networks.

[BibT_eX]

[DOI]

Iurii Kemaev

Daniil Polykovskiy

Proceedings of The 10th Asian Conference on Machine Learning, 2018

Conditional Generators of Words Definitions.

[BibT_eX]

[DOI]

Artyom Gadetsky

Ilya Yakubovskiy

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

2017

Probabilistic Adaptive Computation Time.

[BibT_eX]

[DOI]

Artem Sobolev

CoRR, 2017

Bayesian Sparsification of Recurrent Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2017

Structured Bayesian Pruning via Log-Normal Multiplicative Noise.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Variational Dropout Sparsifies Deep Neural Networks.

[BibT_eX]

[DOI]

Dmitry Molchanov

Arsenii Ashukha

Proceedings of the 34th International Conference on Machine Learning, 2017

Fast Adaptation in Generative Models with Generative Matching Networks.

[BibT_eX]

[DOI]

Sergey Bartunov

Proceedings of the 5th International Conference on Learning Representations, 2017

Spatially Adaptive Computation Time for Residual Networks.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Ultimate tensorization: compressing convolutional and FC layers alike.

[BibT_eX]

[DOI]

CoRR, 2016

Robust Variational Inference.

[BibT_eX]

[DOI]

Kirill Struminsky

CoRR, 2016

GTApprox: Surrogate modeling for industrial design.

[BibT_eX]

[DOI]

Adv. Eng. Softw., 2016

A new approach for sparse Bayesian channel estimation in SCMA uplink systems.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Wireless Communications & Signal Processing, 2016

PerforatedCNNs: Acceleration through Elimination of Redundant Convolutions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Deep Part-Based Generative Shape Model with Latent Variables.

[BibT_eX]

[DOI]

Proceedings of the British Machine Vision Conference 2016, 2016

Breaking Sticks and Ambiguities with Adaptive Skip-gram.

[BibT_eX]

[DOI]

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

Submodular Relaxation for Inference in Markov Random Fields.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2015

PerforatedCNNs: Acceleration through Elimination of Redundant Convolutions.

[BibT_eX]

[DOI]

Pushmeet Kohli

CoRR, 2015

Tensorizing Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

M-Best-Diverse Labelings for Submodular Energies and Beyond.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Inferring M-Best Diverse Labelings in a Single One.

[BibT_eX]

[DOI]

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

2014

Putting MRFs on a Tensor Train.

[BibT_eX]

[DOI]

Proceedings of the 31th International Conference on Machine Learning, 2014

Variational Inference for Sequential Distance Dependent Chinese Restaurant Process.

[BibT_eX]

[DOI]

Sergey Bartunov

Proceedings of the 31th International Conference on Machine Learning, 2014

Multi-utility Learning: Structured-Output Learning with Multiple Annotation-Specific Loss Functions.

[BibT_eX]

[DOI]

Proceedings of the Energy Minimization Methods in Computer Vision and Pattern Recognition, 2014

2013

Машинное обучение - состояние и перспективы (Machine Learning: State of the Art and Perspectives).

[BibT_eX]

[DOI]

Proceedings of the Selected Papers of the 15th All-Russian Scientific Conference "Digital libraries: Advanced Methods and Technologies, 2013

Learning a Model for Shape-Constrained Image Segmentation from Weakly Labeled Data.

[BibT_eX]

[DOI]

Boris Yangel

Proceedings of the Energy Minimization Methods in Computer Vision and Pattern Recognition, 2013

Spatial Inference Machines.

[BibT_eX]

[DOI]

Roman Shapovalov

Pushmeet Kohli

Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

2012

Submodular Relaxation for MRFs with High-Order Potentials.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2012. Workshops and Demonstrations, 2012

2011

Automated atlas-based segmentation of NISSL-stained mouse brain sections using supervised learning.

[BibT_eX]

[DOI]

Olga V. Senyukova

A. S. Lukin

Program. Comput. Softw., 2011

Image Segmentation with a Shape Prior Based on Simplified Skeleton.

[BibT_eX]

[DOI]

Boris Yangel

Proceedings of the Energy Minimazation Methods in Computer Vision and Pattern Recognition, 2011

Submodular decomposition framework for inference in associative Markov networks with global constraints.

[BibT_eX]

[DOI]

Vladimir Kolmogorov

Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

2010

Variational Relevance Vector Machine for Tabular Data.

[BibT_eX]

[DOI]

Proceedings of the 2nd Asian Conference on Machine Learning, 2010

An Interactive Method of Anatomical Segmentation and Gene Expression Estimation for an Experimental Mouse Brain Slice.

[BibT_eX]

[DOI]

Konstantin V. Anokhin

Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2010

2009

ODDboost: Incorporating Posterior Estimates into AdaBoost.

[BibT_eX]

[DOI]

Olga Barinova

Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2009

3-D Mouse Brain Model Reconstruction from a Sequence of 2-D Slices in Application to Allen Brain Atlas.

[BibT_eX]

[DOI]

Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2009

2007

Fuzzy Rules Generation Method for Pattern Recognition Problems.

[BibT_eX]

[DOI]

Proceedings of the Applications of Fuzzy Sets Theory, 2007

On one method of non-diagonal regularization in sparse Bayesian learning.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2007

2006

Evaluation of Stability of k-Means Cluster Ensembles with Respect to Random Initialization.

[BibT_eX]

[DOI]

Ludmila I. Kuncheva

IEEE Trans. Pattern Anal. Mach. Intell., 2006

On Kernel Selection in Relevance Vector Machines Using Stability Principle.

[BibT_eX]

[DOI]

Proceedings of the 18th International Conference on Pattern Recognition (ICPR 2006), 2006

The Use of Stability Principle for Kernel Determination in Relevance Vector Machines.

[BibT_eX]

[DOI]

Proceedings of the Neural Information Processing, 13th International Conference, 2006

2005

The Use of Bayesian Framework for Kernel Selection in Vector Machines Classifiers.

[BibT_eX]

[DOI]

Nikita Ptashko

Proceedings of the Progress in Pattern Recognition, 2005

2004

An Algorithm for Rule Generation in Fuzzy Expert Systems.

[BibT_eX]

[DOI]

Proceedings of the 17th International Conference on Pattern Recognition, 2004

Data Dependent Classifier Fusion for Construction of Stable Effective Algorithms.

[BibT_eX]

[DOI]

Proceedings of the 17th International Conference on Pattern Recognition, 2004

2003

One Approach to Fuzzy Expert Systems Construction.

[BibT_eX]