Alexander Shekhovtsov

Orcid: 0000-0003-0678-8954

According to our database1, Alexander Shekhovtsov authored at least 38 papers between 2004 and 2023.

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Bibliography

2023
Enumerating Complexity Revisited.
Electron. Colloquium Comput. Complex., 2023

Symmetric Equilibrium Learning of VAEs.
CoRR, 2023

Cold Analysis of Rao-Blackwellized Straight-Through Gumbel-Softmax Gradient Estimator.
Proceedings of the International Conference on Machine Learning, 2023

Generalized Differentiable RANSAC.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
VAE Approximation Error: ELBO and Exponential Families.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
VAE Approximation Error: ELBO and Conditional Independence.
CoRR, 2021

Reintroducing Straight-Through Estimators as Principled Methods for Stochastic Binary Networks.
Proceedings of the Pattern Recognition - 43rd DAGM German Conference, DAGM GCPR 2021, Bonn, Germany, September 28, 2021

Bias-Variance Tradeoffs in Single-Sample Binary Gradient Estimators.
Proceedings of the Pattern Recognition - 43rd DAGM German Conference, DAGM GCPR 2021, Bonn, Germany, September 28, 2021

Initialization and Transfer Learning of Stochastic Binary Networks From Real-Valued Ones.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

2020
Reintroducing Straight-Through Estimators as Principled Methods for Stochastic Binary Networks.
CoRR, 2020

Path Sample-Analytic Gradient Estimators for Stochastic Binary Networks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Belief Propagation Reloaded: Learning BP-Layers for Labeling Problems.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Taxonomy of Dual Block-Coordinate Ascent Methods for Discrete Energy Minimization.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Feed-forward Propagation in Probabilistic Neural Networks with Categorical and Max Layers.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Maximum Persistency via Iterative Relaxed Inference in Graphical Models.
IEEE Trans. Pattern Anal. Mach. Intell., 2018

Feed-forward Uncertainty Propagation in Belief and Neural Networks.
CoRR, 2018

Normalization of Neural Networks using Analytic Variance Propagation.
CoRR, 2018

MPLP++: Fast, Parallel Dual Block-Coordinate Ascent for Dense Graphical Models.
Proceedings of the Computer Vision - ECCV 2018, 2018

Stochastic Normalizations as Bayesian Learning.
Proceedings of the Computer Vision - ACCV 2018, 2018

2017
Generative learning for deep networks.
CoRR, 2017

Scalable Full Flow with Learned Binary Descriptors.
Proceedings of the Pattern Recognition - 39th German Conference, 2017

End-to-End Training of Hybrid CNN-CRF Models for Stereo.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016
Partial Optimality by Pruning for MAP-Inference with General Graphical Models.
IEEE Trans. Pattern Anal. Mach. Intell., 2016

Automated integer programming based separation of arteries and veins from thoracic CT images.
Medical Image Anal., 2016

Higher order maximum persistency and comparison theorems.
Comput. Vis. Image Underst., 2016

Solving Dense Image Matching in Real-Time using Discrete-Continuous Optimization.
CoRR, 2016

Joint M-Best-Diverse Labelings as a Parametric Submodular Minimization.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Complexity of Discrete Energy Minimization Problems.
Proceedings of the Computer Vision - ECCV 2016, 2016

2014
Maximum Persistency in Energy Minimization.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2013
A Distributed Mincut/Maxflow Algorithm Combining Path Augmentation and Push-Relabel.
Int. J. Comput. Vis., 2013

2012
Curvature Prior for MRF-Based Segmentation and Shape Inpainting.
Proceedings of the Pattern Recognition, 2012

2011
On Partial Opimality by Auxiliary Submodular Problems
CoRR, 2011

2010
Joint Image GMM and Shading MAP Estimation.
Proceedings of the 20th International Conference on Pattern Recognition, 2010

2009
Scalable multi-view stereo.
Proceedings of the 12th IEEE International Conference on Computer Vision Workshops, 2009

2008
Efficient MRF deformation model for non-rigid image matching.
Comput. Vis. Image Underst., 2008

On partial optimality in multi-label MRFs.
Proceedings of the Machine Learning, 2008

A discrete search method for multi-modal non-rigid image registration.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2008

2004
A Higher Order MRF-Model for Stereo-Reconstruction.
Proceedings of the Pattern Recognition, 26th DAGM Symposium, August 30, 2004


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