Maksym Korablyov

15 papers A* 3Journal 12
YearRankTypeTitle / Venue / Authors
2024 J jnl
Generative Active Learning for the Search of Small-molecule Protein Binders.
CoRR
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, Jarrid Rector-Brooks, Simon Blackburn, Leo Feng, Hadi Nekoei, Sai Krishna Gottipati, Priyesh Vijayan, Prateek Gupta, Ladislav Rampásek, Sasikanth Avancha, Pierre-Luc Bacon, William L. Hamilton, Brooks Paige, Sanchit Misra, Stanislaw Kamil Jastrzebski, Bharat Kaul, Doina Precup, José Miguel Hernández-Lobato, Marwin H. S. Segler, Michael M. Bronstein, Anne Marinier, Mike Tyers, Yoshua Bengio
2024 A* conf
SE(3)-Stochastic Flow Matching for Protein Backbone Generation.
ICLR
Avishek 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
2023 J jnl
DEUP: Direct Epistemic Uncertainty Prediction.
Trans. Mach. Learn. Res.
Salem Lahlou, Moksh Jain, Hadi Nekoei, Victor Butoi, Paul Bertin, Jarrid Rector-Brooks, Maksym Korablyov, Yoshua Bengio
2023 A* conf
Learning GFlowNets From Partial Episodes For Improved Convergence And Stability.
ICML
Kanika Madan, Jarrid Rector-Brooks, Maksym Korablyov, Emmanuel Bengio, Moksh Jain, Andrei Cristian Nica, Tom Bosc, Yoshua Bengio, Nikolay Malkin
2023 J jnl
SE(3)-Stochastic Flow Matching for Protein Backbone Generation.
CoRR
Avishek Joey Bose, Tara Akhound-Sadegh, Kilian Fatras, Guillaume Huguet, Jarrid Rector-Brooks, Cheng-Hao Liu, Andrei Cristian Nica, Maksym Korablyov, Michael M. Bronstein, Alexander Tong
2023 J jnl
Thompson sampling for improved exploration in GFlowNets.
CoRR
Jarrid Rector-Brooks, Kanika Madan, Moksh Jain, Maksym Korablyov, Cheng-Hao Liu, Sarath Chandar, Nikolay Malkin, Yoshua Bengio
2022 J jnl
Learning GFlowNets from partial episodes for improved convergence and stability.
CoRR
Kanika Madan, Jarrid Rector-Brooks, Maksym Korablyov, Emmanuel Bengio, Moksh Jain, Andrei Cristian Nica, Tom Bosc, Yoshua Bengio, Nikolay Malkin
2022 J jnl
RECOVER: sequential model optimization platform for combination drug repurposing identifies novel synergistic compounds in vitro.
CoRR
Paul Bertin, Jarrid Rector-Brooks, Deepak Sharma, Thomas Gaudelet, Andrew Anighoro, Torsten Gross, Francisco Martinez-Pena, Eileen L. Tang, Suraj M. S, Cristian Regep, Jeremy B. R. Hayter, Maksym Korablyov, Nicholas Valiante, Almer van der Sloot, Mike Tyers, Charles Roberts, Michael M. Bronstein, Luke L. Lairson, Jake P. Taylor-King, Yoshua Bengio
2022 J jnl
RetroGNN: Fast Estimation of Synthesizability for Virtual Screening and De Novo Design by Learning from Slow Retrosynthesis Software.
J. Chem. Inf. Model.
Cheng-Hao Liu, Maksym Korablyov, Stanislaw Jastrzebski, Pawel Wlodarczyk-Pruszynski, Yoshua Bengio, Marwin H. S. Segler
2021 J jnl
DEUP: Direct Epistemic Uncertainty Prediction.
CoRR
Moksh Jain, Salem Lahlou, Hadi Nekoei, Victor Butoi, Paul Bertin, Jarrid Rector-Brooks, Maksym Korablyov, Yoshua Bengio
2021 A* conf
Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation.
NeurIPS
Emmanuel Bengio, Moksh Jain, Maksym Korablyov, Doina Precup, Yoshua Bengio
2021 J jnl
Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation.
CoRR
Emmanuel Bengio, Moksh Jain, Maksym Korablyov, Doina Precup, Yoshua Bengio
2021 J jnl
Properties of Minimizing Entropy.
CoRR
Xu Ji, Léna Néhale Ezzine, Maksym Korablyov
2020 J jnl
RetroGNN: Approximating Retrosynthesis by Graph Neural Networks for De Novo Drug Design.
CoRR
Cheng-Hao Liu, Maksym Korablyov, Stanislaw Jastrzebski, Pawel Wlodarczyk-Pruszynski, Yoshua Bengio, Marwin H. S. Segler
2018 J jnl
Capsule networks for low-data transfer learning.
CoRR
Andrew Gritsevskiy, Maksym Korablyov