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Moksh Jain
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2020 – today
- 2024
- [j2]Alex Hernández-García, Nikita Saxena, Moksh Jain, Cheng-Hao Liu, Yoshua Bengio:
Multi-Fidelity Active Learning with GFlowNets. Trans. Mach. Learn. Res. 2024 (2024) - [c13]Edward J. Hu, Moksh Jain, Eric Elmoznino, Younesse Kaddar, Guillaume Lajoie, Yoshua Bengio, Nikolay Malkin:
Amortizing intractable inference in large language models. ICLR 2024 - [c12]Ling Pan, Moksh Jain, Kanika Madan, Yoshua Bengio:
Pre-Training and Fine-Tuning Generative Flow Networks. ICLR 2024 - [c11]Ming-Yang Zhou, Zichao Yan, Elliot Layne, Nikolay Malkin, Dinghuai Zhang, Moksh Jain, Mathieu Blanchette, Yoshua Bengio:
PhyloGFN: Phylogenetic inference with generative flow networks. ICLR 2024 - [i25]Michal Koziarski, Mohammed Abukalam, Vedant Shah, Louis Vaillancourt, Doris Alexandra Schuetz, Moksh Jain, Almer van der Sloot
, Mathieu Bourgey, Anne Marinier, Yoshua Bengio:
Towards DNA-Encoded Library Generation with GFlowNets. CoRR abs/2404.10094 (2024) - [i24]Maksym Korablyov, Cheng-Hao Liu, Moksh Jain, Almer M. van der Sloot
Generative Active Learning for the Search of Small-molecule Protein Binders. CoRR abs/2405.01616 (2024) - [i23]Seanie Lee, Minsu Kim, Lynn Cherif, David Dobre, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Moksh Jain:
Learning diverse attacks on large language models for robust red-teaming and safety tuning. CoRR abs/2405.18540 (2024) - [i22]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:
Amortizing intractable inference in diffusion models for vision, language, and control. CoRR abs/2405.20971 (2024) - [i21]Zuheng Xu, Moksh Jain, Ali Denton, Shawn Whitfield, Aniket Didolkar, Berton Earnshaw, Jason S. Hartford:
Automated Discovery of Pairwise Interactions from Unstructured Data. CoRR abs/2409.07594 (2024) - 2023
- [j1]Salem Lahlou, Moksh Jain, Hadi Nekoei, Victor Butoi, Paul Bertin, Jarrid Rector-Brooks, Maksym Korablyov, Yoshua Bengio:
DEUP: Direct Epistemic Uncertainty Prediction. Trans. Mach. Learn. Res. 2023 (2023) - [c10]Edward J. Hu, Nikolay Malkin, Moksh Jain, Katie E. Everett, Alexandros Graikos, Yoshua Bengio:
GFlowNet-EM for Learning Compositional Latent Variable Models. ICML 2023: 13528-13549 - [c9]Moksh Jain, Sharath Chandra Raparthy, Alex Hernández-García, Jarrid Rector-Brooks, Yoshua Bengio, Santiago Miret, Emmanuel Bengio:
Multi-Objective GFlowNets. ICML 2023: 14631-14653 - [c8]Dianbo Liu, Moksh Jain, Bonaventure F. P. Dossou, Qianli Shen, Salem Lahlou, Anirudh Goyal, Nikolay Malkin, Chris Chinenye Emezue, Dinghuai Zhang, Nadhir Hassen, Xu Ji, Kenji Kawaguchi, Yoshua Bengio:
GFlowOut: Dropout with Generative Flow Networks. ICML 2023: 21715-21729 - [c7]Kanika Madan, Jarrid Rector-Brooks, Maksym Korablyov, Emmanuel Bengio, Moksh Jain, Andrei Cristian Nica, Tom Bosc, Yoshua Bengio, Nikolay Malkin:
Learning GFlowNets From Partial Episodes For Improved Convergence And Stability. ICML 2023: 23467-23483 - [c6]Ling Pan, Dinghuai Zhang, Moksh Jain, Longbo Huang, Yoshua Bengio:
Stochastic Generative Flow Networks. UAI 2023: 1628-1638 - [i20]Moksh Jain, Tristan Deleu, Jason S. Hartford, Cheng-Hao Liu, Alex Hernández-García, Yoshua Bengio:
GFlowNets for AI-Driven Scientific Discovery. CoRR abs/2302.00615 (2023) - [i19]Edward J. Hu, Nikolay Malkin, Moksh Jain, Katie Everett, Alexandros Graikos, Yoshua Bengio:
GFlowNet-EM for learning compositional latent variable models. CoRR abs/2302.06576 (2023) - [i18]Ling Pan, Dinghuai Zhang, Moksh Jain, Longbo Huang, Yoshua Bengio:
Stochastic Generative Flow Networks. CoRR abs/2302.09465 (2023) - [i17]Alex Hernández-García, Nikita Saxena, Moksh Jain, Cheng-Hao Liu, Yoshua Bengio:
Multi-Fidelity Active Learning with GFlowNets. CoRR abs/2306.11715 (2023) - [i16]Shreshth A. Malik, Salem Lahlou, Andrew Jesson, Moksh Jain, Nikolay Malkin, Tristan Deleu, Yoshua Bengio, Yarin Gal:
BatchGFN: Generative Flow Networks for Batch Active Learning. CoRR abs/2306.15058 (2023) - [i15]Jarrid Rector-Brooks, Kanika Madan, Moksh Jain, Maksym Korablyov, Cheng-Hao Liu, Sarath Chandar, Nikolay Malkin, Yoshua Bengio:
Thompson sampling for improved exploration in GFlowNets. CoRR abs/2306.17693 (2023) - [i14]Ling Pan, Moksh Jain, Kanika Madan, Yoshua Bengio:
Pre-Training and Fine-Tuning Generative Flow Networks. CoRR abs/2310.03419 (2023) - [i13]Edward J. Hu, Moksh Jain, Eric Elmoznino, Younesse Kaddar, Guillaume Lajoie, Yoshua Bengio, Nikolay Malkin:
Amortizing intractable inference in large language models. CoRR abs/2310.04363 (2023) - [i12]Mingyang Zhou, Zichao Yan, Elliot Layne, Nikolay Malkin, Dinghuai Zhang, Moksh Jain, Mathieu Blanchette, Yoshua Bengio:
PhyloGFN: Phylogenetic inference with generative flow networks. CoRR abs/2310.08774 (2023) - 2022
- [c5]Moksh Jain, Emmanuel Bengio, Alex Hernández-García, Jarrid Rector-Brooks, Bonaventure F. P. Dossou, Chanakya Ajit Ekbote, Jie Fu, Tianyu Zhang, Michael Kilgour, Dinghuai Zhang, Lena Simine, Payel Das, Yoshua Bengio:
Biological Sequence Design with GFlowNets. ICML 2022: 9786-9801 - [c4]Nikolay Malkin, Moksh Jain, Emmanuel Bengio, Chen Sun, Yoshua Bengio:
Trajectory balance: Improved credit assignment in GFlowNets. NeurIPS 2022 - [i11]Nikolay Malkin, Moksh Jain, Emmanuel Bengio, Chen Sun, Yoshua Bengio:
Trajectory Balance: Improved Credit Assignment in GFlowNets. CoRR abs/2201.13259 (2022) - [i10]Moksh Jain, Emmanuel Bengio, Alex Hernández-García, Jarrid Rector-Brooks, Bonaventure F. P. Dossou, Chanakya Ekbote, Jie Fu, Tianyu Zhang, Michael Kilgour
Biological Sequence Design with GFlowNets. CoRR abs/2203.04115 (2022) - [i9]Kanika Madan, Jarrid Rector-Brooks, Maksym Korablyov, Emmanuel Bengio, Moksh Jain, Andrei Cristian Nica, Tom Bosc, Yoshua Bengio, Nikolay Malkin:
Learning GFlowNets from partial episodes for improved convergence and stability. CoRR abs/2209.12782 (2022) - [i8]Bonaventure F. P. Dossou, Dianbo Liu, Xu Ji, Moksh Jain, Almer M. van der Sloot, Roger Palou, Michael Tyers, Yoshua Bengio:
Graph-Based Active Machine Learning Method for Diverse and Novel Antimicrobial Peptides Generation and Selection. CoRR abs/2209.13518 (2022) - [i7]Moksh Jain, Sharath Chandra Raparthy, Alex Hernández-García, Jarrid Rector-Brooks, Yoshua Bengio, Santiago Miret, Emmanuel Bengio:
Multi-Objective GFlowNets. CoRR abs/2210.12765 (2022) - [i6]Dianbo Liu, Moksh Jain, Bonaventure Dossou, Qianli Shen, Salem Lahlou, Anirudh Goyal, Nikolay Malkin, Chris Emezue, Dinghuai Zhang, Nadhir Hassen, Xu Ji, Kenji Kawaguchi, Yoshua Bengio:
GFlowOut: Dropout with Generative Flow Networks. CoRR abs/2210.12928 (2022) - [i5]Chanakya Ekbote, Moksh Jain, Payel Das, Yoshua Bengio:
Consistent Training via Energy-Based GFlowNets for Modeling Discrete Joint Distributions. CoRR abs/2211.00568 (2022) - 2021
- [c3]Emmanuel Bengio, Moksh Jain, Maksym Korablyov, Doina Precup, Yoshua Bengio:
Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation. NeurIPS 2021: 27381-27394 - [i4]Moksh Jain, Salem Lahlou, Hadi Nekoei, Victor Butoi, Paul Bertin, Jarrid Rector-Brooks, Maksym Korablyov, Yoshua Bengio:
DEUP: Direct Epistemic Uncertainty Prediction. CoRR abs/2102.08501 (2021) - [i3]Emmanuel Bengio, Moksh Jain, Maksym Korablyov, Doina Precup, Yoshua Bengio:
Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation. CoRR abs/2106.04399 (2021) - 2020
- [c2]Moksh Jain, S. Sowmya Kamath
Improving Convergence in IRGAN with PPO. COMAD/CODS 2020: 328-329 - [c1]Sachin Goyal, Aditi Raghunathan, Moksh Jain, Harsha Vardhan Simhadri, Prateek Jain:
DROCC: Deep Robust One-Class Classification. ICML 2020: 3711-3721 - [i2]Sachin Goyal, Aditi Raghunathan, Moksh Jain, Harsha Vardhan Simhadri, Prateek Jain:
DROCC: Deep Robust One-Class Classification. CoRR abs/2002.12718 (2020)
2010 – 2019
- 2019
- [i1]Moksh Jain, Sowmya Kamath S.:
Proximal Policy Optimization for Improved Convergence in IRGAN. CoRR abs/1910.00352 (2019)
Coauthor Index
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