A Quantum-Inspired Ensemble Method and Quantum-Inspired Forest Regressors. - Zeke Xie; Issei Sato (ACML, 2017)

A Diffusion Theory for Deep Learning Dynamics: Stochastic Gradient Descent Escapes From Sharp Minima Exponentially Fast. - Zeke Xie; Issei Sato; Masashi Sugiyama (CoRR, 2020)

Adai: Separating the Effects of Adaptive Learning Rate and Momentum Inertia. - Zeke Xie; Xinrui Wang; Huishuai Zhang; Issei Sato; Masashi Sugiyama (CoRR, 2020)

Stable Weight Decay Regularization. - Zeke Xie; Issei Sato; Masashi Sugiyama (CoRR, 2020)

A Diffusion Theory For Deep Learning Dynamics: Stochastic Gradient Descent Exponentially Favors Flat Minima. - Zeke Xie; Issei Sato; Masashi Sugiyama (ICLR, 2021)

Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization. - Zeke Xie; Li Yuan; Zhanxing Zhu; Masashi Sugiyama (ICML, 2021)

Artificial Neural Variability for Deep Learning: On Overfitting, Noise Memorization, and Catastrophic Forgetting. - Zeke Xie; Fengxiang He; Shaopeng Fu; Issei Sato; Dacheng Tao; Masashi Sugiyama (Neural Comput., 2021)

Sparse Double Descent: Where Network Pruning Aggravates Overfitting. - Zheng He; Zeke Xie; Quanzhi Zhu; Zengchang Qin (ICML, 2022)

Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum. - Zeke Xie; Xinrui Wang; Huishuai Zhang; Issei Sato; Masashi Sugiyama (ICML, 2022)

On the Power-Law Spectrum in Deep Learning: A Bridge to Protein Science. - Zeke Xie; Qian-Yuan Tang 001; Yunfeng Cai; Mingming Sun 001; Ping Li 001 (CoRR, 2022)

Rethinking the Structure of Stochastic Gradients: Empirical and Statistical Evidence. - Zeke Xie; Qian-Yuan Tang 001; Zheng He; Mingming Sun 001; Ping Li 001 (CoRR, 2022)

S3IM: Stochastic Structural SIMilarity and Its Unreasonable Effectiveness for Neural Fields. - Zeke Xie; Xindi Yang; Yujie Yang; Qi Sun; Yixiang Jiang; Haoran Wang 004; Yunfeng Cai; Mingming Sun 001 (ICCV, 2023)

Dataset Pruning: Reducing Training Data by Examining Generalization Influence. - Shuo Yang 006; Zeke Xie; Hanyu Peng; Min Xu 001; Mingming Sun 001; Ping Li 001 (ICLR, 2023)

On the Overlooked Structure of Stochastic Gradients. - Zeke Xie; Qian-Yuan Tang 001; Mingming Sun 001; Ping Li 001 (NeurIPS, 2023)

On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective. - Zeke Xie; Zhiqiang Xu; Jingzhao Zhang; Issei Sato; Masashi Sugiyama (NeurIPS, 2023)

Neural Field Classifiers via Target Encoding and Classification Loss. - Xindi Yang; Zeke Xie; Xiong Zhou; Boyu Liu; Buhua Liu; Yi Liu; Haoran Wang 004; Yunfeng Cai; Mingming Sun 001 (ICLR, 2024)

Variance-enlarged Poisson Learning for Graph-based Semi-Supervised Learning with Extremely Sparse Labeled Data. - Xiong Zhou; Xianming Liu; Hao Yu; Jialiang Wang 003; Zeke Xie; Junjun Jiang; Xiangyang Ji (ICLR, 2024)

HiCAST: Highly Customized Arbitrary Style Transfer with Adapter Enhanced Diffusion Models. - Hanzhang Wang; Haoran Wang 004; Jinze Yang; Zhongrui Yu; Zeke Xie; Lei Tian; Xinyan Xiao; Junjun Jiang; Xianming Liu; Mingming Sun 001 (CoRR, 2024)

SGD: Street View Synthesis with Gaussian Splatting and Diffusion Prior. - Zhongrui Yu; Haoran Wang 004; Jinze Yang; Hanzhang Wang; Zeke Xie; Yunfeng Cai; Jiale Cao; Zhong Ji; Mingming Sun 001 (CoRR, 2024)

VIP: Versatile Image Outpainting Empowered by Multimodal Large Language Model. - Jinze Yang; Haoran Wang 004; Zining Zhu 004; Chenglong Liu; Meng Wymond Wu; Zeke Xie; Zhong Ji; Jungong Han; Mingming Sun 001 (CoRR, 2024)

Converging Paradigms: The Synergy of Symbolic and Connectionist AI in LLM-Empowered Autonomous Agents. - Haoyi Xiong; Zhiyuan Wang 003; Xuhong Li 002; Jiang Bian 003; Zeke Xie; Shahid Mumtaz; Laura E. Barnes (CoRR, 2024)

Not All Noises Are Created Equally:Diffusion Noise Selection and Optimization. - Zipeng Qi; Lichen Bai; Haoyi Xiong; Zeke Xie (CoRR, 2024)

Channel-wise Influence: Estimating Data Influence for Multivariate Time Series. - Muyao Wang; Zeke Xie; Bo Chen (CoRR, 2024)

Alignment of Diffusion Models: Fundamentals, Challenges, and Future. - Buhua Liu; Shitong Shao; Bao Li; Lichen Bai; Zhiqiang Xu; Haoyi Xiong; James Kwok; Sumi Helal; Zeke Xie (CoRR, 2024)

IV-Mixed Sampler: Leveraging Image Diffusion Models for Enhanced Video Synthesis. - Shitong Shao; Zikai Zhou; Lichen Bai; Haoyi Xiong; Zeke Xie (CoRR, 2024)

Pre-trained Molecular Language Models with Random Functional Group Masking. - Tianhao Peng 002; Yuchen Li 006; Xuhong Li 002; Jiang Bian 003; Zeke Xie; Ning Sui; Shahid Mumtaz; Yanwu Xu 001; Linghe Kong; Haoyi Xiong (CoRR, 2024)

Golden Noise for Diffusion Models: A Learning Framework. - Zikai Zhou; Shitong Shao; Lichen Bai; Zhiqiang Xu; Bo Han; Zeke Xie (CoRR, 2024)

Bag of Design Choices for Inference of High-Resolution Masked Generative Transformer. - Shitong Shao; Zikai Zhou; Tian Ye 001; Lichen Bai; Zhiqiang Xu; Zeke Xie (CoRR, 2024)

A Simple and Efficient Baseline for Zero-Shot Generative Classification. - Zipeng Qi; Buhua Liu; Shiyan Zhang; Bao Li; Zhiqiang Xu; Haoyi Xiong; Zeke Xie (CoRR, 2024)

Mono2Stereo: A Benchmark and Empirical Study for Stereo Conversion. - Songsong Yu; Yuxin Chen; Zhongang Qi; Zeke Xie; Yifan Wang 004; Lijun Wang; Ying Shan; Huchuan Lu (CVPR, 2025)

Diffusion Models are Zero-Shot Generative Text-Vision Retrievers. - Bao Li; Zeke Xie; Xiaomei Zhang; Xiangyu Zhu 001; Zhen Lei 001 (ICASSP, 2025)

Learning from Ambiguous Data with Hard Labels. - Zeke Xie; Zheng He; Nan Lu; Lichen Bai; Bao Li; Shuo Yang 006; Mingming Sun 001; Ping Li 001 (ICASSP, 2025)

Zigzag Diffusion Sampling: Diffusion Models Can Self-Improve via Self-Reflection. - Lichen Bai; Shitong Shao; Zikai Zhou; Zipeng Qi; Zhiqiang Xu; Haoyi Xiong; Zeke Xie (ICLR, 2025)

IV-mixed Sampler: Leveraging Image Diffusion Models for Enhanced Video Synthesis. - Shitong Shao; Zikai Zhou; Bai Lichen; Haoyi Xiong; Zeke Xie (ICLR, 2025)

Stronger Separability, Stronger Defense: Influence-Based Backdoor Detection. - Buhua Liu; Shuo Yang; Zhiqiang Xu; Haoyi Xiong; Yiu-ming Cheung; Zeke Xie (PAKDD (1), 2025)

Weak-to-Strong Diffusion with Reflection. - Lichen Bai; Masashi Sugiyama; Zeke Xie (CoRR, 2025)

Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples. - Chengqian Gao; Haonan Li; Liu Liu 014; Zeke Xie; Peilin Zhao; Zhiqiang Xu 003 (CoRR, 2025)

MagicInfinite: Generating Infinite Talking Videos with Your Words and Voice. - Hongwei Yi; Tian Ye 001; Shitong Shao; Xuancheng Yang; Jiantong Zhao; Hanzhong Guo; Terrance Wang; Qingyu Yin; Zeke Xie; Lei Zhu 003; Wei Li 049; Michael Lingelbach; et al. (CoRR, 2025)

CoRe2: Collect, Reflect and Refine to Generate Better and Faster. - Shitong Shao; Zikai Zhou; Dian Xie; Yuetong Fang; Tian Ye 001; Lichen Bai; Zeke Xie (CoRR, 2025)

MagicDistillation: Weak-to-Strong Video Distillation for Large-Scale Few-Step Synthesis. - Shitong Shao; Hongwei Yi; Hanzhong Guo; Tian Ye 001; Daquan Zhou; Michael Lingelbach; Zhiqiang Xu; Zeke Xie (CoRR, 2025)

DSADF: Thinking Fast and Slow for Decision Making. - Alex Zhihao Dou; Dongfei Cui; Jun Yan; Weida Wang; Benteng Chen; Haoming Wang; Zeke Xie; Shufei Zhang (CoRR, 2025)

Multiphysics Bench: Benchmarking and Investigating Scientific Machine Learning for Multiphysics PDEs. - Changfan Yang; Lichen Bai; Yinpeng Wang; Shufei Zhang; Zeke Xie (CoRR, 2025)

Diffusion Dataset Condensation: Training Your Diffusion Model Faster with Less Data. - Rui Huang; Shitong Shao; Zikai Zhou; Pukun Zhao; Hangyu Guo; Tian Ye 001; Lichen Bai; Shuo Yang; Zeke Xie (CoRR, 2025)

Understanding Data Influence with Differential Approximation. - Haoru Tan; Sitong Wu; Xiuzhe Wu; Wang Wang; Bo Zhao; Zeke Xie; Gui-Song Xia; Xiaojuan Qi 001 (CoRR, 2025)