GNN-based concentration prediction for random microfluidic mixers. - Weiqing Ji; Xingzhuo Guo; Shouan Pan; Tsung-Yi Ho; Ulf Schlichtmann; Hailong Yao (DAC, 2022)

HermEs: Interactive Spreadsheet Formula Prediction via Hierarchical Formulet Expansion. - Wanrong He; Haoyu Dong 001; Yihuai Gao; Zhichao Fan; Xingzhuo Guo; Zhitao Hou; Xiao Lv; Ran Jia; Shi Han; Dongmei Zhang 001 (ACL (1), 2023)

Estimating Heterogeneous Treatment Effects: Mutual Information Bounds and Learning Algorithms. - Xingzhuo Guo; Yuchen Zhang 004; Jianmin Wang 001; Mingsheng Long (ICML, 2023)

CLIPood: Generalizing CLIP to Out-of-Distributions. - Yang Shu 001; Xingzhuo Guo; Jialong Wu 001; Ximei Wang; Jianmin Wang 001; Mingsheng Long (ICML, 2023)

Decoupled Training: Return of Frustratingly Easy Multi-Domain Learning. - Ximei Wang; Junwei Pan; Xingzhuo Guo; Dapeng Liu; Jie Jiang 015 (AAAI, 2024)

CogDPM: Diffusion Probabilistic Models via Cognitive Predictive Coding. - Kaiyuan Chen; Xingzhuo Guo; Yu Zhang; Jianmin Wang 001; Mingsheng Long (ICML, 2024)

On the Embedding Collapse when Scaling up Recommendation Models. - Xingzhuo Guo; Junwei Pan; Ximei Wang; Baixu Chen; Jie Jiang 015; Mingsheng Long (ICML, 2024)

Diffusion Tuning: Transferring Diffusion Models via Chain of Forgetting. - Jincheng Zhong; Xingzhuo Guo; Jiaxiang Dong; Mingsheng Long (NeurIPS, 2024)

GNN-Based Concentration Prediction With Variable Input Flow Rates for Microfluidic Mixers. - Weiqing Ji; Xingzhuo Guo; Shouan Pan; Fei Long; Tsung-Yi Ho; Ulf Schlichtmann; Hailong Yao (IEEE Trans. Biomed. Circuits Syst., 2024)

Dynamical Diffusion: Learning Temporal Dynamics with Diffusion Models. - Xingzhuo Guo; Yu Zhang; Baixu Chen; Haoran Xu; Jianmin Wang 001; Mingsheng Long (ICLR, 2025)

Consistent World Models via Foresight Diffusion. - Yu Zhang; Xingzhuo Guo; Haoran Xu; Mingsheng Long (CoRR, 2025)