Alexander Shekhovtsov | DeepAI

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∙ 07/19/2023

Symmetric Equilibrium Learning of VAEs

We view variational autoencoders (VAE) as decoder-encoder pairs, which m...

0 Boris Flach, et al. ∙

∙ 10/07/2021

Bias-Variance Tradeoffs in Single-Sample Binary Gradient Estimators

Discrete and especially binary random variables occur in many machine le...

0 Alexander Shekhovtsov, et al. ∙

∙ 02/18/2021

VAE Approximation Error: ELBO and Conditional Independence

The importance of Variational Autoencoders reaches far beyond standalone...

0 Dmitrij Schlesinger, et al. ∙

∙ 06/11/2020

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

Training neural networks with binary weights and activations is a challe...

0 Viktor Yanush, et al. ∙

∙ 06/04/2020

Path Sample-Analytic Gradient Estimators for Stochastic Binary Networks

In networks with binary activations and or binary weights the training b...

0 Alexander Shekhovtsov, et al. ∙

∙ 04/16/2020

MPLP++: Fast, Parallel Dual Block-Coordinate Ascent for Dense Graphical Models

Dense, discrete Graphical Models with pairwise potentials are a powerful...

0 Siddharth Tourani, et al. ∙

∙ 04/16/2020

Taxonomy of Dual Block-Coordinate Ascent Methods for Discrete Energy Minimization

We consider the maximum-a-posteriori inference problem in discrete graph...

0 Siddharth Tourani, et al. ∙

∙ 03/13/2020

Belief Propagation Reloaded: Learning BP-Layers for Labeling Problems

It has been proposed by many researchers that combining deep neural netw...

2 Patrick Knöbelreiter, et al. ∙

∙ 11/01/2018

Stochastic Normalizations as Bayesian Learning

In this work we investigate the reasons why Batch Normalization (BN) imp...

0 Alexander Shekhovtsov, et al. ∙

∙ 03/28/2018

Feed-forward Uncertainty Propagation in Belief and Neural Networks

We propose a feed-forward inference method applicable to belief and neur...

0 Alexander Shekhovtsov, et al. ∙

∙ 03/28/2018

Normalization of Neural Networks using Analytic Variance Propagation

We address the problem of estimating statistics of hidden units in a neu...

0 Alexander Shekhovtsov, et al. ∙

∙ 09/25/2017

Generative learning for deep networks

Learning, taking into account full distribution of the data, referred to...

0 Boris Flach, et al. ∙

∙ 07/20/2017

Scalable Full Flow with Learned Binary Descriptors

We propose a method for large displacement optical flow in which local m...

0 Gottfried Munda, et al. ∙

∙ 11/30/2016

End-to-End Training of Hybrid CNN-CRF Models for Stereo

We propose a novel and principled hybrid CNN+CRF model for stereo estima...

0 Patrick Knöbelreiter, et al. ∙

∙ 07/29/2016

Complexity of Discrete Energy Minimization Problems

Discrete energy minimization is widely-used in computer vision and machi...

0 Mengtian Li, et al. ∙

∙ 06/22/2016

Joint M-Best-Diverse Labelings as a Parametric Submodular Minimization

We consider the problem of jointly inferring the M-best diverse labeling...

0 Alexander Kirillov, et al. ∙

∙ 01/23/2016

Solving Dense Image Matching in Real-Time using Discrete-Continuous Optimization

Dense image matching is a fundamental low-level problem in Computer Visi...

0 Alexander Shekhovtsov, et al. ∙

∙ 08/31/2015

Maximum Persistency via Iterative Relaxed Inference with Graphical Models

We consider the NP-hard problem of MAP-inference for undirected discrete...

0 Alexander Shekhovtsov, et al. ∙

∙ 05/04/2015

Higher Order Maximum Persistency and Comparison Theorems

We address combinatorial problems that can be formulated as minimization...

0 Alexander Shekhovtsov, et al. ∙

∙ 10/24/2014

Partial Optimality by Pruning for MAP-Inference with General Graphical Models

We consider the energy minimization problem for undirected graphical mod...

0 Paul Swoboda, et al. ∙

∙ 09/07/2011

Curvature Prior for MRF-based Segmentation and Shape Inpainting

Most image labeling problems such as segmentation and image reconstructi...

0 Alexander Shekhovtsov, et al. ∙

∙ 09/06/2011

On Partial Opimality by Auxiliary Submodular Problems

In this work, we prove several relations between three different energy ...

0 Alexander Shekhovtsov, et al. ∙

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