Han, Jiaqi

29 publications

ICLR 2026 Align Your Structures: Generating Trajectories with Structure Pretraining for Molecular Dynamics Aniketh Iyengar, Jiaqi Han, Pengwei Sun, Mingjian Jiang, Jianwen Xie, Stefano Ermon

ICLR 2026 Discrete Diffusion Trajectory Alignment via Stepwise Decomposition Jiaqi Han, Austin Wang, Minkai Xu, Wenda Chu, Meihua Dang, Haotian Ye, Huayu Chen, Yisong Yue, Stefano Ermon

ICLR 2026 InfoTok: Adaptive Discrete Video Tokenizer via Information-Theoretic Compression Haotian Ye, Qiyuan He, Jiaqi Han, Puheng Li, Jiaojiao Fan, Zekun Hao, Fitsum Reda, Yogesh Balaji, Huayu Chen, Sheng Liu, Angela Yao, James Zou, Stefano Ermon, Haoxiang Wang, Ming-Yu Liu

ICLR 2026 PRISM-Physics: Causal DAG-Based Process Evaluation for Physics Reasoning Wanjia Zhao, Qinwei Ma, Jingzhe Shi, Shirley Wu, Jiaqi Han, Yijia Xiao, Si-Yuan Chen, Xiao Luo, Ludwig Schmidt, James Zou

ICLR 2026 Principled RL for Diffusion LLMs Emerges from a Sequence-Level Perspective Jingyang Ou, Jiaqi Han, Minkai Xu, Shaoxuan Xu, Jianwen Xie, Stefano Ermon, Yi Wu, Chongxuan Li

AISTATS 2025 $f$-PO: Generalizing Preference Optimization with $f$-Divergence Minimization Jiaqi Han, Mingjian Jiang, Yuxuan Song, Stefano Ermon, Minkai Xu

ICLR 2025 Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models Marianne Arriola, Aaron Gokaslan, Justin T Chiu, Zhihan Yang, Zhixuan Qi, Jiaqi Han, Subham Sekhar Sahoo, Volodymyr Kuleshov

ICCV 2025 CHORDS: Diffusion Sampling Accelerator with Multi-Core Hierarchical ODE Solvers Jiaqi Han, Haotian Ye, Puheng Li, Minkai Xu, James Zou, Stefano Ermon

ICLR 2025 CPSample: Classifier Protected Sampling for Guarding Training Data During Diffusion Joshua Kazdan, Hao Sun, Jiaqi Han, Felix Petersen, Frederick Vu, Stefano Ermon

NeurIPS 2025 GeoAda: Efficiently Finetune Geometric Diffusion Models with Equivariant Adapters Wanjia Zhao, Jiaqi Han, Siyi Gu, Mingjian Jiang, James Zou, Stefano Ermon

ICML 2025 Zero-Shot Cyclic Peptide Design via Composable Geometric Constraints Dapeng Jiang, Xiangzhe Kong, Jiaqi Han, Mingyu Li, Rui Jiao, Wenbing Huang, Stefano Ermon, Jianzhu Ma, Yang Liu

NeurIPSW 2024 CPSample: Classifier Protected Sampling for Guarding Training Data During Diffusion Joshua Kazdan, Hao Sun, Jiaqi Han, Felix Petersen, Frederick Vu, Stefano Ermon

ICMLW 2024 Energy-Free Guidance of Geometric Diffusion Models for 3D Molecule Inverse Design Aksh Garg, Jiaqi Han, Sanjay Nagaraj, Minkai Xu

ICMLW 2024 Energy-Free Guidance of Geometric Diffusion Models for 3D Molecule Inverse Design Sanjay Nagaraj, Jiaqi Han, Aksh Garg, Minkai Xu

ICMLW 2024 Energy-Free Guidance of Geometric Diffusion Models for 3D Molecule Inverse Design Jiaqi Han, Aksh Garg, Sanjay Nagaraj, Minkai Xu

ICML 2024 Equivariant Graph Neural Operator for Modeling 3D Dynamics Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar

NeurIPS 2024 Geometric Trajectory Diffusion Models Jiaqi Han, Minkai Xu, Aaron Lou, Haotian Ye, Stefano Ermon

ICML 2024 Improving Equivariant Graph Neural Networks on Large Geometric Graphs via Virtual Nodes Learning Yuelin Zhang, Jiacheng Cen, Jiaqi Han, Zhiqiang Zhang, Jun Zhou, Wenbing Huang

NeurIPS 2024 RelBench: A Benchmark for Deep Learning on Relational Databases Joshua Robinson, Rishabh Ranjan, Weihua Hu, Kexin Huang, Jiaqi Han, Alejandro Dobles, Matthias Fey, Jan E. Lenssen, Yiwen Yuan, Zecheng Zhang, Xinwei He, Jure Leskovec

NeurIPSW 2024 Relational Deep Learning: Graph Representation Learning on Relational Databases Joshua Robinson, Rishabh Ranjan, Weihua Hu, Kexin Huang, Jiaqi Han, Alejandro Dobles, Matthias Fey, Jan Eric Lenssen, Yiwen Yuan, Zecheng Zhang, Xinwei He, Jure Leskovec

NeurIPS 2024 TFG: Unified Training-Free Guidance for Diffusion Models Haotian Ye, Haowei Lin, Jiaqi Han, Minkai Xu, Sheng Liu, Yitao Liang, Jianzhu Ma, James Zou, Stefano Ermon

NeurIPS 2023 Crystal Structure Prediction by Joint Equivariant Diffusion Rui Jiao, Wenbing Huang, Peijia Lin, Jiaqi Han, Pin Chen, Yutong Lu, Yang Liu

ICLRW 2023 Crystal Structure Prediction by Joint Equivariant Diffusion on Lattices and Fractional Coordinates Rui Jiao, Wenbing Huang, Peijia Lin, Jiaqi Han, Pin Chen, Yutong Lu, Yang Liu

AAAI 2023 Energy-Motivated Equivariant Pretraining for 3D Molecular Graphs Rui Jiao, Jiaqi Han, Wenbing Huang, Yu Rong, Yang Liu

ICML 2023 Subequivariant Graph Reinforcement Learning in 3D Environments Runfa Chen, Jiaqi Han, Fuchun Sun, Wenbing Huang

NeurIPS 2022 Equivariant Graph Hierarchy-Based Neural Networks Jiaqi Han, Wenbing Huang, Tingyang Xu, Yu Rong

NeurIPSW 2022 Equivariant Graph Hierarchy-Based Neural Networks Jiaqi Han, Yu Rong, Tingyang Xu, Wenbing Huang

ICLR 2022 Equivariant Graph Mechanics Networks with Constraints Wenbing Huang, Jiaqi Han, Yu Rong, Tingyang Xu, Fuchun Sun, Junzhou Huang

NeurIPS 2022 Learning Physical Dynamics with Subequivariant Graph Neural Networks Jiaqi Han, Wenbing Huang, Hengbo Ma, Jiachen Li, Josh Tenenbaum, Chuang Gan