| Biological sequence design with gflownets M Jain, E Bengio, A Hernandez-Garcia, J Rector-Brooks, BFP Dossou, ... International Conference on Machine Learning, 9786-9801, 2022 | 103 | 2022 |
| Deup: Direct epistemic uncertainty prediction S Lahlou, M Jain, H Nekoei, VI Butoi, P Bertin, J Rector-Brooks, ... arXiv preprint arXiv:2102.08501, 2021 | 74 | 2021 |
| Improving and generalizing flow-based generative models with minibatch optimal transport A Tong, N Malkin, G Huguet, Y Zhang, J Rector-Brooks, K Fatras, G Wolf, ... arXiv preprint arXiv:2302.00482, 2023 | 65* | 2023 |
| Learning GFlowNets from partial episodes for improved convergence and stability K Madan, J Rector-Brooks, M Korablyov, E Bengio, M Jain, AC Nica, ... International Conference on Machine Learning, 23467-23483, 2023 | 37 | 2023 |
| Multi-objective gflownets M Jain, SC Raparthy, A Hernández-Garcıa, J Rector-Brooks, Y Bengio, ... International conference on machine learning, 14631-14653, 2023 | 34 | 2023 |
| Thompson sampling for improved exploration in GFlowNets J Rector-Brooks, K Madan, M Jain, M Korablyov, CH Liu, S Chandar, ... arXiv preprint arXiv:2306.17693, 2023 | 10 | 2023 |
| Se (3)-stochastic flow matching for protein backbone generation AJ Bose, T Akhound-Sadegh, K Fatras, G Huguet, J Rector-Brooks, ... arXiv preprint arXiv:2310.02391, 2023 | 8 | 2023 |
| Recover: sequential model optimization platform for combination drug repurposing identifies novel synergistic compounds in vitro P Bertin, J Rector-Brooks, D Sharma, T Gaudelet, A Anighoro, T Gross, ... arXiv preprint arXiv:2202.04202, 2022 | 8 | 2022 |
| Revisiting projection-free optimization for strongly convex constraint sets J Rector-Brooks, JK Wang, B Mozafari Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 1576-1583, 2019 | 6 | 2019 |
| RECOVER identifies synergistic drug combinations in vitro through sequential model optimization P Bertin, J Rector-Brooks, D Sharma, T Gaudelet, A Anighoro, T Gross, ... Cell Reports Methods 3 (10), 2023 | 5 | 2023 |
| Molecular fragment-based diffusion model for drug discovery D Levy, J Rector-Brooks ICLR 2023-Machine Learning for Drug Discovery workshop, 2023 | 3 | 2023 |
| Iterated Denoising Energy Matching for Sampling from Boltzmann Densities T Akhound-Sadegh*, J Rector-Brooks*, AJ Bose*, S Mittal, P Lemos, ... arXiv preprint arXiv:2402.06121, 2024 | 1 | 2024 |
| Learning Conditional Policies for Crystal Design Using Offline Reinforcement Learning P Govindarajan, S Miret, J Rector-Brooks, M Phielipp, J Rajendran, ... Digital Discovery, 2024 | 1 | 2024 |
| Behavioral cloning for crystal design P Govindarajan, S Miret, J Rector-Brooks, M Phielipp, J Rajendran, ... Workshop on''Machine Learning for Materials''ICLR 2023, 2023 | 1 | 2023 |
| On diffusion models for amortized inference: Benchmarking and improving stochastic control and sampling M Sendera, M Kim, S Mittal, P Lemos, L Scimeca, J Rector-Brooks, ... arXiv preprint arXiv:2402.05098, 2024 | | 2024 |
| Integrating Generative and Experimental Platforms or Biomolecular Design CH Liu, J Rector-Brooks, J Yim, S Yang, S Lisanza, FZ Li, P Chatterjee, ... ICLR 2024 Workshops, 0 | | |
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
