Korablyov, Maksym

6 publications

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

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

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

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

ICLRW 2022 Evaluating Generalization in GFlowNets for Molecule Design Andrei Cristian Nica, Moksh Jain, Emmanuel Bengio, Cheng-Hao Liu, Maksym Korablyov, Michael M. Bronstein, Yoshua Bengio

NeurIPS 2021 Flow Network Based Generative Models for Non-Iterative Diverse Candidate Generation Emmanuel Bengio, Moksh Jain, Maksym Korablyov, Doina Precup, Yoshua Bengio