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ORCIDRob Brekelmans
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2020 – today
- 2024
[c12]Kirill Neklyudov, Rob Brekelmans, Alexander Tong, Lazar Atanackovic, Qiang Liu, Alireza Makhzani:
A Computational Framework for Solving Wasserstein Lagrangian Flows. ICML 2024- [c11]Stephen Zhao, Rob Brekelmans, Alireza Makhzani, Roger Baker Grosse:
Probabilistic Inference in Language Models via Twisted Sequential Monte Carlo. ICML 2024 - [i19]Stephen Zhao, Rob Brekelmans, Alireza Makhzani, Roger B. Grosse:
Probabilistic Inference in Language Models via Twisted Sequential Monte Carlo. CoRR abs/2404.17546 (2024) - [i18]Yuanqi Du, Michael Plainer, Rob Brekelmans, Chenru Duan, Frank Noé, Carla P. Gomes, Alán Aspuru-Guzik, Kirill Neklyudov:
Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling. CoRR abs/2410.07974 (2024) - [i17]Haibo Wang, Yuxuan Qiu, Yanze Wang, Rob Brekelmans, Yuanqi Du:
Generalized Flow Matching for Transition Dynamics Modeling. CoRR abs/2410.15128 (2024) - 2023
- [c10]Xianghao Kong, Rob Brekelmans, Greg Ver Steeg:
Information-Theoretic Diffusion. ICLR 2023 - [c9]Kirill Neklyudov
, Rob Brekelmans, Daniel Severo, Alireza Makhzani:
Action Matching: Learning Stochastic Dynamics from Samples. ICML 2023: 25858-25889 - [i16]Xianghao Kong, Rob Brekelmans, Greg Ver Steeg:
Information-Theoretic Diffusion. CoRR abs/2302.03792 (2023) - [i15]Rob Brekelmans, Sicong Huang, Marzyeh Ghassemi, Greg Ver Steeg, Roger B. Grosse, Alireza Makhzani:
Improving Mutual Information Estimation with Annealed and Energy-Based Bounds. CoRR abs/2303.06992 (2023) - [i14]Kirill Neklyudov, Rob Brekelmans, Alexander Tong, Lazar Atanackovic, Qiang Liu, Alireza Makhzani:
A Computational Framework for Solving Wasserstein Lagrangian Flows. CoRR abs/2310.10649 (2023) - 2022
- [j1]Rob Brekelmans, Tim Genewein, Jordi Grau-Moya, Grégoire Delétang, Markus Kunesch, Shane Legg, Pedro A. Ortega:
Your Policy Regularizer is Secretly an Adversary. Trans. Mach. Learn. Res. 2022 (2022) - [c8]Rob Brekelmans, Sicong Huang, Marzyeh Ghassemi, Greg Ver Steeg, Roger Baker Grosse, Alireza Makhzani:
Improving Mutual Information Estimation with Annealed and Energy-Based Bounds. ICLR 2022 - [i13]Rob Brekelmans, Tim Genewein, Jordi Grau-Moya, Grégoire Delétang, Markus Kunesch, Shane Legg, Pedro A. Ortega:
Your Policy Regularizer is Secretly an Adversary. CoRR abs/2203.12592 (2022) - [i12]Rob Brekelmans, Frank Nielsen:
Rho-Tau Bregman Information and the Geometry of Annealing Paths. CoRR abs/2209.07481 (2022) - 2021
- [c7]Vaden Masrani, Rob Brekelmans, Thang Bui, Frank Nielsen, Aram Galstyan, Greg Ver Steeg, Frank Wood:
q-Paths: Generalizing the geometric annealing path using power means. UAI 2021: 1938-1947 - [i11]Vaden Masrani, Rob Brekelmans, Thang Bui, Frank Nielsen, Aram Galstyan, Greg Ver Steeg, Frank Wood:
q-Paths: Generalizing the Geometric Annealing Path using Power Means. CoRR abs/2107.00745 (2021) - [i10]Grégoire Delétang, Jordi Grau-Moya, Markus Kunesch, Tim Genewein, Rob Brekelmans, Shane Legg, Pedro A. Ortega:
Model-Free Risk-Sensitive Reinforcement Learning. CoRR abs/2111.02907 (2021) - 2020
- [c6]Rob Brekelmans, Vaden Masrani, Frank Wood, Greg Ver Steeg, Aram Galstyan:
All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference. ICML 2020: 1111-1122 - [c5]Vu Nguyen, Vaden Masrani, Rob Brekelmans, Michael A. Osborne, Frank Wood:
Gaussian Process Bandit Optimization of the Thermodynamic Variational Objective. NeurIPS 2020 - [i9]Rob Brekelmans, Vaden Masrani, Frank Wood, Greg Ver Steeg, Aram Galstyan:
All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference. CoRR abs/2007.00642 (2020) - [i8]Vu Nguyen, Vaden Masrani, Rob Brekelmans, Michael A. Osborne, Frank Wood:
Gaussian Process Bandit Optimization of theThermodynamic Variational Objective. CoRR abs/2010.15750 (2020) - [i7]Rob Brekelmans, Vaden Masrani, Thang Bui, Frank Wood, Aram Galstyan, Greg Ver Steeg, Frank Nielsen:
Annealed Importance Sampling with q-Paths. CoRR abs/2012.07823 (2020) - [i6]Rob Brekelmans, Frank Nielsen, Alireza Makhzani, Aram Galstyan, Greg Ver Steeg:
Likelihood Ratio Exponential Families. CoRR abs/2012.15480 (2020)
2010 – 2019
- 2019
- [c4]Shuyang Gao, Rob Brekelmans, Greg Ver Steeg, Aram Galstyan:
Auto-Encoding Total Correlation Explanation. AISTATS 2019: 1157-1166 - [c3]Rob Brekelmans, Daniel Moyer, Aram Galstyan, Greg Ver Steeg:
Exact Rate-Distortion in Autoencoders via Echo Noise. NeurIPS 2019: 3884-3895 - [i5]Rob Brekelmans, Daniel Moyer, Aram Galstyan, Greg Ver Steeg:
Exact Rate-Distortion in Autoencoders via Echo Noise. CoRR abs/1904.07199 (2019) - [i4]Ayush Jaiswal, Rob Brekelmans, Daniel Moyer, Greg Ver Steeg, Wael AbdAlmageed, Premkumar Natarajan:
Discovery and Separation of Features for Invariant Representation Learning. CoRR abs/1912.00646 (2019) - 2018
- [c2]Daniel Moyer, Shuyang Gao, Rob Brekelmans, Aram Galstyan, Greg Ver Steeg:
Invariant Representations without Adversarial Training. NeurIPS 2018: 9102-9111 - [i3]Shuyang Gao, Rob Brekelmans, Greg Ver Steeg, Aram Galstyan:
Auto-Encoding Total Correlation Explanation. CoRR abs/1802.05822 (2018) - [i2]Daniel Moyer, Shuyang Gao, Rob Brekelmans, Greg Ver Steeg, Aram Galstyan:
Evading the Adversary in Invariant Representation. CoRR abs/1805.09458 (2018) - 2017
- [c1]Greg Ver Steeg, Rob Brekelmans, Hrayr Harutyunyan, Aram Galstyan:
Disentangled representations via synergy minimization. Allerton 2017: 180-187 - [i1]Greg Ver Steeg, Rob Brekelmans, Hrayr Harutyunyan, Aram Galstyan:
Disentangled Representations via Synergy Minimization. CoRR abs/1710.03839 (2017)
Coauthor Index
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