Liu, Cheng-Hao

18 publications

ICLR 2026 Battery Fault: A Comprehensive Dataset and Benchmark for Battery Fault Diagnosis Qingdi Liu, Yan Fu, Lishuo Liu, Yanke Lin, Jin Xin, Jianfeng Zhang, Cheng Hao Liu, Lujia Pan, Dongxu Guo, Yuejiu Zheng, Qiang Li

ICLR 2026 OXtal: An All-Atom Diffusion Model for Organic Crystal Structure Prediction Emily Jin, Andrei Cristian Nica, Mikhail Galkin, Jarrid Rector-Brooks, Kin Long Kelvin Lee, Santiago Miret, Frances H. Arnold, Michael M. Bronstein, Joey Bose, Alexander Tong, Cheng-Hao Liu

ICLR 2026 SynCoGen: Synthesizable 3D Molecule Generation via Joint Reaction and Coordinate Modeling Andrei Rekesh, Miruna Cretu, Dmytro Shevchuk, Pietro Lio, Robert A. Batey, Mike Tyers, Michał Koziarski, Cheng-Hao Liu

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