Rector-Brooks, Jarrid

21 publications

TMLR 2026 From Discrete-Time Policies to Continuous-Time Diffusion Samplers: Asymptotic Equivalences and Faster Training Julius Berner, Lorenz Richter, Marcin Sendera, Jarrid Rector-Brooks, Nikolay Malkin

ICLR 2025 Adaptive Teachers for Amortized Samplers Minsu Kim, Sanghyeok Choi, Taeyoung Yun, Emmanuel Bengio, Leo Feng, Jarrid Rector-Brooks, Sungsoo Ahn, Jinkyoo Park, Nikolay Malkin, Yoshua Bengio

ICLRW 2025 Path Planning for Masked Diffusion Models with Applications to Biological Sequence Generation Fred Zhangzhi Peng, Zachary Bezemek, Sawan Patel, Jarrid Rector-Brooks, Sherwood Yao, Alexander Tong, Pranam Chatterjee

ICLR 2025 Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction Jarrid Rector-Brooks, Mohsin Hasan, Zhangzhi Peng, Cheng-Hao Liu, Sarthak Mittal, Nouha Dziri, Michael M. Bronstein, Pranam Chatterjee, Alexander Tong, Joey Bose

NeurIPS 2024 Amortizing Intractable Inference in Diffusion Models for Vision, Language, and Control Siddarth Venkatraman, Moksh Jain, Luca Scimeca, Minsu Kim, Marcin Sendera, Mohsin Hasan, Luke Rowe, Sarthak Mittal, Pablo Lemos, Emmanuel Bengio, Alexandre Adam, Jarrid Rector-Brooks, Yoshua Bengio, Glen Berseth, Nikolay Malkin

NeurIPS 2024 Improved Off-Policy Training of Diffusion Samplers Marcin Sendera, Minsu Kim, Sarthak Mittal, Pablo Lemos, Luca Scimeca, Jarrid Rector-Brooks, Alexandre Adam, Yoshua Bengio, Nikolay Malkin

TMLR 2024 Improving and Generalizing Flow-Based Generative Models with Minibatch Optimal Transport Alexander Tong, Kilian Fatras, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Guy Wolf, Yoshua Bengio

ICML 2024 Iterated Denoising Energy Matching for Sampling from Boltzmann Densities Tara Akhound-Sadegh, Jarrid Rector-Brooks, Joey Bose, Sarthak Mittal, Pablo Lemos, Cheng-Hao Liu, Marcin Sendera, Siamak Ravanbakhsh, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Alexander Tong

ICLR 2024 SE(3)-Stochastic Flow Matching for Protein Backbone Generation Joey Bose, Tara Akhound-Sadegh, Guillaume Huguet, Kilian Fatras, Jarrid Rector-Brooks, Cheng-Hao Liu, Andrei Cristian Nica, Maksym Korablyov, Michael M. Bronstein, Alexander Tong

NeurIPS 2024 Sequence-Augmented SE(3)-Flow Matching for Conditional Protein Generation Guillaume Huguet, James Vuckovic, Kilian Fatras, Eric Thibodeau-Laufer, Pablo Lemos, Riashat Islam, Cheng-Hao Liu, Jarrid Rector-Brooks, Tara Akhound-Sadegh, Michael Bronstein, Alexander Tong, Avishek Joey Bose

ICLRW 2023 Behavioral Cloning for Crystal Design Prashant Govindarajan, Santiago Miret, Jarrid Rector-Brooks, Mariano Phielipp, Janarthanan Rajendran, Sarath Chandar

TMLR 2023 DEUP: Direct Epistemic Uncertainty Prediction Salem Lahlou, Moksh Jain, Hadi Nekoei, Victor I Butoi, Paul Bertin, Jarrid Rector-Brooks, Maksym Korablyov, Yoshua Bengio

ICMLW 2023 Improving and Generalizing Flow-Based Generative Models with Minibatch Optimal Transport Alexander Tong, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Kilian Fatras, Guy Wolf, Yoshua Bengio

NeurIPSW 2023 Learning Conditional Policies for Crystal Design Using Offline Reinforcement Learning Prashant Govindarajan, Santiago Miret, Jarrid Rector-Brooks, Mariano Phielipp, Janarthanan Rajendran, Sarath Chandar

ICML 2023 Learning GFlowNets from Partial Episodes for Improved Convergence and Stability Kanika Madan, Jarrid Rector-Brooks, Maksym Korablyov, Emmanuel Bengio, Moksh Jain, Andrei Cristian Nica, Tom Bosc, Yoshua Bengio, Nikolay Malkin

ICLRW 2023 Molecular Fragment-Based Diffusion Model for Drug Discovery Daniel Levy, Jarrid Rector-Brooks

ICML 2023 Multi-Objective GFlowNets Moksh Jain, Sharath Chandra Raparthy, Alex Hernández-Garcı́a, Jarrid Rector-Brooks, Yoshua Bengio, Santiago Miret, Emmanuel Bengio

ICMLW 2023 Thompson Sampling for Improved Exploration in GFlowNets Jarrid Rector-Brooks, Kanika Madan, Moksh Jain, Maksym Korablyov, Cheng-Hao Liu, Sarath Chandar, Nikolay Malkin, Yoshua Bengio

ICML 2022 Biological Sequence Design with GFlowNets Moksh Jain, Emmanuel Bengio, Alex Hernandez-Garcia, Jarrid Rector-Brooks, Bonaventure F. P. Dossou, Chanakya Ajit Ekbote, Jie Fu, Tianyu Zhang, Michael Kilgour, Dinghuai Zhang, Lena Simine, Payel Das, Yoshua Bengio

NeurIPSW 2022 Multi-Objective GFlowNets Moksh Jain, Sharath Chandra Raparthy, Alex Hernández-García, Jarrid Rector-Brooks, Yoshua Bengio, Santiago Miret, Emmanuel Bengio

AAAI 2019 Revisiting Projection-Free Optimization for Strongly Convex Constraint Sets Jarrid Rector-Brooks, Jun-Kun Wang, Barzan Mozafari