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Cheng-Hao Liu
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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) - [c3]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:
SE(3)-Stochastic Flow Matching for Protein Backbone Generation. ICLR 2024 - [c2]Dinghuai Zhang, Ricky T. Q. Chen, Cheng-Hao Liu, Aaron C. Courville, Yoshua Bengio:
Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization. ICLR 2024 - [c1]Tara Akhound-Sadegh, Jarrid Rector-Brooks, Avishek Joey Bose, Sarthak Mittal, Pablo Lemos, Cheng-Hao Liu, Marcin Sendera, Siamak Ravanbakhsh, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Alexander Tong:
Iterated Denoising Energy Matching for Sampling from Boltzmann Densities. ICML 2024 - [i13]Tara Akhound-Sadegh, Jarrid Rector-Brooks, Avishek Joey Bose, Sarthak Mittal, Pablo Lemos, Cheng-Hao Liu, Marcin Sendera, Siamak Ravanbakhsh, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Alexander Tong:
Iterated Denoising Energy Matching for Sampling from Boltzmann Densities. CoRR abs/2402.06121 (2024) - [i12]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:
Generative Active Learning for the Search of Small-molecule Protein Binders. CoRR abs/2405.01616 (2024) - [i11]Guillaume Huguet, James Vuckovic, Kilian Fatras, Eric Thibodeau-Laufer, Pablo Lemos, Riashat Islam, Cheng-Hao Liu, Jarrid Rector-Brooks, Tara Akhound-Sadegh, Michael M. Bronstein, Alexander Tong, Avishek Joey Bose:
Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Backbone Generation. CoRR abs/2405.20313 (2024) - [i10]Chunhui Li, Cheng-Hao Liu, Dianbo Liu, Qingpeng Cai, Ling Pan:
Bifurcated Generative Flow Networks. CoRR abs/2406.01901 (2024) - [i9]Michal Koziarski, Andrei Rekesh, Dmytro Shevchuk, Almer van der Sloot
RGFN: Synthesizable Molecular Generation Using GFlowNets. CoRR abs/2406.08506 (2024) - [i8]Jarrid Rector-Brooks, Mohsin Hasan, Zhangzhi Peng, Zachary Quinn, Cheng-Hao Liu, Sarthak Mittal, Nouha Dziri, Michael M. Bronstein, Yoshua Bengio, Pranam Chatterjee, Alexander Tong, Avishek Joey Bose:
Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction. CoRR abs/2410.08134 (2024) - 2023
- [i7]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) - [i6]Alex Hernández-García, Nikita Saxena, Moksh Jain, Cheng-Hao Liu, Yoshua Bengio:
Multi-Fidelity Active Learning with GFlowNets. CoRR abs/2306.11715 (2023) - [i5]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) - [i4]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
SE(3)-Stochastic Flow Matching for Protein Backbone Generation. CoRR abs/2310.02391 (2023) - [i3]Dinghuai Zhang, Ricky Tian Qi Chen, Cheng-Hao Liu, Aaron C. Courville, Yoshua Bengio:
Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization. CoRR abs/2310.02679 (2023) - [i2]Alexandra Volokhova, Michal Koziarski, Alex Hernández-García, Cheng-Hao Liu, Santiago Miret, Pablo Lemos, Luca A. Thiede, Zichao Yan, Alán Aspuru-Guzik
Towards equilibrium molecular conformation generation with GFlowNets. CoRR abs/2310.14782 (2023) - 2022
- [j1]Cheng-Hao Liu
RetroGNN: Fast Estimation of Synthesizability for Virtual Screening and De Novo Design by Learning from Slow Retrosynthesis Software. J. Chem. Inf. Model. 62(10): 2293-2300 (2022) - 2020
- [i1]Cheng-Hao Liu
RetroGNN: Approximating Retrosynthesis by Graph Neural Networks for De Novo Drug Design. CoRR abs/2011.13042 (2020)
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