Brekelmans, Rob

26 publications

ICML 2025 Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts Marta Skreta, Tara Akhound-Sadegh, Viktor Ohanesian, Roberto Bondesan, Alan Aspuru-Guzik, Arnaud Doucet, Rob Brekelmans, Alexander Tong, Kirill Neklyudov

ICLRW 2025 Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts Marta Skreta, Tara Akhound-Sadegh, Viktor Ohanesian, Roberto Bondesan, Alan Aspuru-Guzik, Arnaud Doucet, Rob Brekelmans, Alexander Tong, Kirill Neklyudov

NeurIPS 2025 Reducing the Probability of Undesirable Outputs in Language Models Using Probabilistic Inference Stephen Zhao, Aidan Li, Rob Brekelmans, Roger Baker Grosse

ICLRW 2025 Scaling Deep Learning Solutions for Transition Path Sampling Jungyoon Lee, Michael Plainer, Yuanqi Du, Lars Holdijk, Rob Brekelmans, Dominique Beaini, Kirill Neklyudov

ICLRW 2025 Scaling Deep Learning Solutions for Transition Path Sampling Jungyoon Lee, Michael Plainer, Yuanqi Du, Lars Holdijk, Rob Brekelmans, Carla P Gomes, Dominique Beaini, Kirill Neklyudov

ICML 2024 A Computational Framework for Solving Wasserstein Lagrangian Flows Kirill Neklyudov, Rob Brekelmans, Alexander Tong, Lazar Atanackovic, Qiang Liu, Alireza Makhzani

NeurIPS 2024 Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling Yuanqi Du, Michael Plainer, Rob Brekelmans, Chenru Duan, Frank Noé, Carla P. Gomes, Alán Aspuru-Guzik, Kirill Neklyudov

ICMLW 2024 Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling Yuanqi Du, Michael Plainer, Rob Brekelmans, Chenru Duan, Frank Noe, Carla P Gomes, Alan Aspuru-Guzik, Kirill Neklyudov

ICMLW 2024 Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling Yuanqi Du, Michael Plainer, Rob Brekelmans, Chenru Duan, Frank Noe, Carla P Gomes, Alan Aspuru-Guzik, Kirill Neklyudov

ICMLW 2024 Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling Yuanqi Du, Michael Plainer, Rob Brekelmans, Chenru Duan, Frank Noe, Carla P Gomes, Alan Aspuru-Guzik, Kirill Neklyudov

NeurIPSW 2024 Generalized Flow Matching for Transition Dynamics Modeling Haibo Wang, Yuxuan Qiu, Yanze Wang, Rob Brekelmans, Yuanqi Du

ICML 2024 Probabilistic Inference in Language Models via Twisted Sequential Monte Carlo Stephen Zhao, Rob Brekelmans, Alireza Makhzani, Roger Baker Grosse

NeurIPSW 2023 A Computational Framework for Solving Wasserstein Lagrangian Flows Kirill Neklyudov, Rob Brekelmans, Alexander Tong, Lazar Atanackovic, Qiang Liu, Alireza Makhzani

ICML 2023 Action Matching: Learning Stochastic Dynamics from Samples Kirill Neklyudov, Rob Brekelmans, Daniel Severo, Alireza Makhzani

ICLR 2023 Information-Theoretic Diffusion Xianghao Kong, Rob Brekelmans, Greg Ver Steeg

NeurIPSW 2023 On Schrödinger Bridge Matching and Expectation Maximization Rob Brekelmans, Kirill Neklyudov

ICLR 2022 Improving Mutual Information Estimation with Annealed and Energy-Based Bounds Rob Brekelmans, Sicong Huang, Marzyeh Ghassemi, Greg Ver Steeg, Roger Baker Grosse, Alireza Makhzani

TMLR 2022 Your Policy Regularizer Is Secretly an Adversary Rob Brekelmans, Tim Genewein, Jordi Grau-Moya, Gregoire Detetang, Markus Kunesch, Shane Legg, Pedro A Ortega

UAI 2021 Q-Paths: Generalizing the Geometric Annealing Path Using Power Means Vaden Masrani, Rob Brekelmans, Thang Bui, Frank Nielsen, Aram Galstyan, Greg Ver Steeg, Frank Wood

ICML 2020 All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference Rob Brekelmans, Vaden Masrani, Frank Wood, Greg Ver Steeg, Aram Galstyan

NeurIPSW 2020 Annealed Importance Sampling with Q-Paths Rob Brekelmans, Vaden Masrani, Thang D Bui, Frank Wood, Aram Galstyan, Greg Ver Steeg, Frank Nielsen

NeurIPS 2020 Gaussian Process Bandit Optimization of the Thermodynamic Variational Objective Vu Nguyen, Vaden Masrani, Rob Brekelmans, Michael Osborne, Frank Wood

NeurIPSW 2020 Likelihood Ratio Exponential Families Rob Brekelmans, Frank Nielsen, Alireza Makhzani, Aram Galstyan, Greg Ver Steeg

AISTATS 2019 Auto-Encoding Total Correlation Explanation Shuyang Gao, Rob Brekelmans, Greg Ver Steeg, Aram Galstyan

NeurIPS 2019 Exact Rate-Distortion in Autoencoders via Echo Noise Rob Brekelmans, Daniel Moyer, Aram Galstyan, Greg Ver Steeg

NeurIPS 2018 Invariant Representations Without Adversarial Training Daniel Moyer, Shuyang Gao, Rob Brekelmans, Aram Galstyan, Greg Ver Steeg