Liu, Cheng-Hao

15 publications

AAAI 2025 Flow Factorization for Efficient Generative Flow Networks Jiashun Liu, Chunhui Li, Cheng-Hao Liu, Dianbo Liu, Qingpeng Cai, Ling Pan

ICLRW 2025 Generating $\pi$-Functional Molecules Using STGG+ with Active Learning Alexia Jolicoeur-Martineau, Yan Zhang, Boris Knyazev, Aristide Baratin, Cheng-Hao Liu

ICLR 2025 Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction Jarrid Rector-Brooks, Mohsin Hasan, Zhangzhi Peng, Cheng-Hao Liu, Sarthak Mittal, Nouha Dziri, Michael M. Bronstein, Pranam Chatterjee, Alexander Tong, Joey Bose

ICLRW 2025 Substrate-Aware Zero-Shot Predictors for Non-Native Enzyme Activities Francesca-Zhoufan Li, Lukas Alexander Radtke, Kadina E Johnston, Cheng-Hao Liu, Yisong Yue, Frances H. Arnold

ICLR 2024 Diffusion Generative Flow Samplers: Improving Learning Signals Through Partial Trajectory Optimization Dinghuai Zhang, Ricky T. Q. Chen, Cheng-Hao Liu, Aaron Courville, Yoshua Bengio

ICML 2024 Iterated Denoising Energy Matching for Sampling from Boltzmann Densities Tara Akhound-Sadegh, Jarrid Rector-Brooks, Joey Bose, Sarthak Mittal, Pablo Lemos, Cheng-Hao Liu, Marcin Sendera, Siamak Ravanbakhsh, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Alexander Tong

TMLR 2024 Multi-Fidelity Active Learning with GFlowNets Alex Hernández-García, Nikita Saxena, Moksh Jain, Cheng-Hao Liu, Yoshua Bengio

NeurIPS 2024 RGFN: Synthesizable Molecular Generation Using GFlowNets Michał Koziarski, Andrei Rekesh, Dmytro Shevchuk, Almer van der Sloot, Piotr Gaiński, Yoshua Bengio, Cheng-Hao Liu, Mike Tyers, Robert A. Batey

ICMLW 2024 RGFN: Synthesizable Molecular Generation Using GFlowNets Michał Koziarski, Andrei Rekesh, Dmytro Shevchuk, Almer M. van der Sloot, Piotr Gaiński, Yoshua Bengio, Cheng-Hao Liu, Mike Tyers, Robert A. Batey

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

NeurIPS 2024 Sequence-Augmented SE(3)-Flow Matching for Conditional Protein Generation Guillaume Huguet, James Vuckovic, Kilian Fatras, Eric Thibodeau-Laufer, Pablo Lemos, Riashat Islam, Cheng-Hao Liu, Jarrid Rector-Brooks, Tara Akhound-Sadegh, Michael Bronstein, Alexander Tong, Avishek Joey Bose

NeurIPSW 2023 Multi-Fidelity Active Learning with GFlowNets Alex Hernández-García, Nikita Saxena, Moksh Jain, Cheng-Hao Liu, Yoshua Bengio

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

NeurIPSW 2023 Towards Equilibrium Molecular Conformation Generation with GFlowNets Alexandra Volokhova, Michał Koziarski, Alex Hernández-García, Cheng-Hao Liu, Santiago Miret, Pablo Lemos, Luca Thiede, Zichao Yan, Alan Aspuru-Guzik, 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