Rob Brekelmans

According to our database¹, Rob Brekelmans authored at least 20 papers between 2017 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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On csauthors.net:

Bibliography

2024

Probabilistic Inference in Language Models via Twisted Sequential Monte Carlo.

[BibT_eX]

[DOI]

CoRR, 2024

2023

A Computational Framework for Solving Wasserstein Lagrangian Flows.

[BibT_eX]

[DOI]

CoRR, 2023

Action Matching: Learning Stochastic Dynamics from Samples.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Information-Theoretic Diffusion.

[BibT_eX]

[DOI]

Xianghao Kong

Rob Brekelmans

Greg Ver Steeg

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Your Policy Regularizer is Secretly an Adversary.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2022

Rho-Tau Bregman Information and the Geometry of Annealing Paths.

[BibT_eX]

[DOI]

Rob Brekelmans

Frank Nielsen

CoRR, 2022

Improving Mutual Information Estimation with Annealed and Energy-Based Bounds.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Model-Free Risk-Sensitive Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2021

q-Paths: Generalizing the geometric annealing path using power means.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2020

Likelihood Ratio Exponential Families.

[BibT_eX]

[DOI]

CoRR, 2020

Annealed Importance Sampling with q-Paths.

[BibT_eX]

[DOI]

CoRR, 2020

Gaussian Process Bandit Optimization of theThermodynamic Variational Objective.

[BibT_eX]

[DOI]

CoRR, 2020

Gaussian Process Bandit Optimization of the Thermodynamic Variational Objective.

[BibT_eX]

[DOI]

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

All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference.

[BibT_eX]

[DOI]

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

2019

Discovery and Separation of Features for Invariant Representation Learning.

[BibT_eX]

[DOI]

CoRR, 2019

Exact Rate-Distortion in Autoencoders via Echo Noise.

[BibT_eX]

[DOI]

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

Auto-Encoding Total Correlation Explanation.

[BibT_eX]

[DOI]

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

2018

Evading the Adversary in Invariant Representation.

[BibT_eX]

[DOI]

CoRR, 2018

Invariant Representations without Adversarial Training.

[BibT_eX]

[DOI]

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

2017

Disentangled representations via synergy minimization.

[BibT_eX]

[DOI]

Proceedings of the 55th Annual Allerton Conference on Communication, 2017

Rob Brekelmans

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