Proximal Policy Optimization for Improved Convergence in IRGAN. - Moksh Jain; Sowmya Kamath S. (CoRR, 2019)

Improving Convergence in IRGAN with PPO. - Moksh Jain; S. Sowmya Kamath (COMAD/CODS, 2020)

DROCC: Deep Robust One-Class Classification. - Sachin Goyal; Aditi Raghunathan; Moksh Jain; Harsha Vardhan Simhadri; Prateek Jain 002 (ICML, 2020)

Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation. - Emmanuel Bengio; Moksh Jain; Maksym Korablyov; Doina Precup; Yoshua Bengio (NeurIPS, 2021)

Biological Sequence Design with GFlowNets. - Moksh Jain; Emmanuel Bengio; Alex Hernández-García; Jarrid Rector-Brooks; Bonaventure F. P. Dossou; Chanakya Ajit Ekbote; Jie Fu 001; Tianyu Zhang; Michael Kilgour; Dinghuai Zhang; Lena Simine; Payel Das; et al. (ICML, 2022)

Trajectory balance: Improved credit assignment in GFlowNets. - Nikolay Malkin; Moksh Jain; Emmanuel Bengio; Chen Sun 007; Yoshua Bengio (NeurIPS, 2022)

Graph-Based Active Machine Learning Method for Diverse and Novel Antimicrobial Peptides Generation and Selection. - Bonaventure F. P. Dossou; Dianbo Liu; Xu Ji; Moksh Jain; Almer M. van der Sloot; Roger Palou; Michael Tyers; Yoshua Bengio (CoRR, 2022)

Consistent Training via Energy-Based GFlowNets for Modeling Discrete Joint Distributions. - Chanakya Ekbote; Moksh Jain; Payel Das; Yoshua Bengio (CoRR, 2022)

GFlowNet-EM for Learning Compositional Latent Variable Models. - Edward J. Hu; Nikolay Malkin; Moksh Jain; Katie E. Everett; Alexandros Graikos; Yoshua Bengio (ICML, 2023)

Multi-Objective GFlowNets. - Moksh Jain; Sharath Chandra Raparthy; Alex Hernández-García; Jarrid Rector-Brooks; Yoshua Bengio; Santiago Miret; Emmanuel Bengio (ICML, 2023)

GFlowOut: Dropout with Generative Flow Networks. - 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; et al. (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 (ICML, 2023)

Stochastic Generative Flow Networks. - Ling Pan; Dinghuai Zhang; Moksh Jain; Longbo Huang; Yoshua Bengio (UAI, 2023)

GFlowNets for AI-Driven Scientific Discovery. - Moksh Jain; Tristan Deleu; Jason S. Hartford; Cheng-Hao Liu; Alex Hernández-García; Yoshua Bengio (CoRR, 2023)

BatchGFN: Generative Flow Networks for Batch Active Learning. - Shreshth A. Malik; Salem Lahlou; Andrew Jesson; Moksh Jain; Nikolay Malkin; Tristan Deleu; Yoshua Bengio; Yarin Gal (CoRR, 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 (CoRR, 2023)

DEUP: Direct Epistemic Uncertainty Prediction. - Salem Lahlou; Moksh Jain; Hadi Nekoei; Victor Butoi; Paul Bertin; Jarrid Rector-Brooks; Maksym Korablyov; Yoshua Bengio (Trans. Mach. Learn. Res., 2023)

Amortizing intractable inference in large language models. - Edward J. Hu; Moksh Jain; Eric Elmoznino; Younesse Kaddar; Guillaume Lajoie; Yoshua Bengio; Nikolay Malkin (ICLR, 2024)

Pre-Training and Fine-Tuning Generative Flow Networks. - Ling Pan; Moksh Jain; Kanika Madan; Yoshua Bengio (ICLR, 2024)

PhyloGFN: Phylogenetic inference with generative flow networks. - Ming-Yang Zhou; Zichao Yan; Elliot Layne; Nikolay Malkin; Dinghuai Zhang; Moksh Jain; Mathieu Blanchette; Yoshua Bengio (ICLR, 2024)

Amortizing intractable inference in diffusion models for vision, language, and control. - Siddarth Venkatraman; Moksh Jain; Luca Scimeca; Minsu Kim 004; Marcin Sendera; Mohsin Hasan; Luke Rowe; Sarthak Mittal; Pablo Lemos; Emmanuel Bengio; Alexandre Adam; Jarrid Rector-Brooks; et al. (NeurIPS, 2024)

Towards DNA-Encoded Library Generation with GFlowNets. - Michal Koziarski; Mohammed Abukalam; Vedant Shah; Louis Vaillancourt; Doris Alexandra Schuetz; Moksh Jain; Almer van der Sloot; Mathieu Bourgey; Anne Marinier; Yoshua Bengio (CoRR, 2024)

Generative Active Learning for the Search of Small-molecule Protein Binders. - Maksym Korablyov; Cheng-Hao Liu; Moksh Jain; Almer M. van der Sloot; Eric Jolicoeur; Edward Ruediger; Andrei Cristian Nica; Emmanuel Bengio; Kostiantyn Lapchevskyi; Daniel St-Cyr; Doris Alexandra Schuetz; Victor Ion Butoi; et al. (CoRR, 2024)

Automated Discovery of Pairwise Interactions from Unstructured Data. - Zuheng Xu; Moksh Jain; Ali Denton; Shawn Whitfield; Aniket Didolkar; Berton Earnshaw; Jason S. Hartford (CoRR, 2024)

Proof Flow: Preliminary Study on Generative Flow Network Language Model Tuning for Formal Reasoning. - Matthew Ho; Vincent Zhu; Xiaoyin Chen; Moksh Jain; Nikolay Malkin; Edwin Zhang (CoRR, 2024)

Multi-Fidelity Active Learning with GFlowNets. - Alex Hernández-García; Nikita Saxena; Moksh Jain; Cheng-Hao Liu; Yoshua Bengio (Trans. Mach. Learn. Res., 2024)

Action abstractions for amortized sampling. - Oussama Boussif; Léna Néhale Ezzine; Joseph D. Viviano; Michal Koziarski; Moksh Jain; Nikolay Malkin; Emmanuel Bengio; Rim Assouel; Yoshua Bengio (ICLR, 2025)

Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning. - Seanie Lee; Minsu Kim 004; Lynn Cherif; David Dobre; Juho Lee 001; Sung Ju Hwang; Kenji Kawaguchi; Gauthier Gidel; Yoshua Bengio; Nikolay Malkin; Moksh Jain (ICLR, 2025)

Solving Bayesian inverse problems with diffusion priors and off-policy RL. - Luca Scimeca; Siddarth Venkatraman; Moksh Jain; Minsu Kim 004; Marcin Sendera; Mohsin Hasan; Luke Rowe; Sarthak Mittal; Pablo Lemos; Emmanuel Bengio; Alexandre Adam; Jarrid Rector-Brooks; et al. (CoRR, 2025)

Trajectory Balance with Asynchrony: Decoupling Exploration and Learning for Fast, Scalable LLM Post-Training. - Brian R. Bartoldson; Siddarth Venkatraman; James Diffenderfer; Moksh Jain; Tal Ben-Nun; Seanie Lee; Minsu Kim 004; Johan S. Obando-Ceron; Yoshua Bengio; Bhavya Kailkhura (CoRR, 2025)

Search-Based Correction of Reasoning Chains for Language Models. - Minsu Kim 004; Jean-Pierre R. Falet; Oliver E. Richardson; Xiaoyin Chen; Moksh Jain; Sungjin Ahn; Sungsoo Ahn; Yoshua Bengio (CoRR, 2025)