Hu, Jerry Yao-Chieh

27 publications

ICLR 2026 In-Context Algorithm Emulation in Fixed-Weight Transformers Jerry Yao-Chieh Hu, Hude Liu, Jennifer Yuntong Zhang, Han Liu

NeurIPS 2025 Attention Mechanism, Max-Affine Partition, and Universal Approximation Hude Liu, Jerry Yao-Chieh Hu, Zhao Song, Han Liu

ICLR 2025 Computational Limits of Low-Rank Adaptation (LoRA) Fine-Tuning for Transformer Models Jerry Yao-Chieh Hu, Maojiang Su, En-jui Kuo, Zhao Song, Han Liu

ICLRW 2025 Computational Limits of Low-Rank Adaptation (LoRA) Fine-Tuning for Transformer Models Jerry Yao-Chieh Hu, Maojiang Su, En-Jui Kuo, Zhao Song, Han Liu

ICML 2025 Fast and Low-Cost Genomic Foundation Models via Outlier Removal Haozheng Luo, Chenghao Qiu, Maojiang Su, Zhihan Zhou, Zoe Mehta, Guo Ye, Jerry Yao-Chieh Hu, Han Liu

ICLR 2025 Fundamental Limits of Prompt Tuning Transformers: Universality, Capacity and Efficiency Jerry Yao-Chieh Hu, Wei-Po Wang, Ammar Gilani, Chenyang Li, Zhao Song, Han Liu

ICLRW 2025 Fundamental Limits of Prompt Tuning Transformers: Universality, Capacity and Efficiency Jerry Yao-Chieh Hu, Wei-Po Wang, Ammar Gilani, Chenyang Li, Zhao Song, Han Liu

NeurIPS 2025 High-Order Flow Matching: Unified Framework and Sharp Statistical Rates Maojiang Su, Jerry Yao-Chieh Hu, Yi-Chen Lee, Ning Zhu, Jui-Hui Chung, Shang Wu, Zhao Song, Minshuo Chen, Han Liu

ICML 2025 In-Context Deep Learning via Transformer Models Weimin Wu, Maojiang Su, Jerry Yao-Chieh Hu, Zhao Song, Han Liu

ICML 2025 In-Context Learning as Conditioned Associative Memory Retrieval Weimin Wu, Teng-Yun Hsiao, Jerry Yao-Chieh Hu, Wenxin Zhang, Han Liu

ICML 2025 Latent Variable Estimation in Bayesian Black-Litterman Models Thomas Yuan-Lung Lin, Jerry Yao-Chieh Hu, Paul W. Chiou, Peter Lin

ICML 2025 Nonparametric Modern Hopfield Models Jerry Yao-Chieh Hu, Bo-Yu Chen, Dennis Wu, Feng Ruan, Han Liu

ICLR 2025 On Statistical Rates of Conditional Diffusion Transformers: Approximation, Estimation and Minimax Optimality Jerry Yao-Chieh Hu, Weimin Wu, Yi-Chen Lee, Yu-Chao Huang, Minshuo Chen, Han Liu

NeurIPS 2025 Pareto-Optimal Energy Alignment for Designing Nature-like Antibodies Yibo Wen, Chenwei Xu, Jerry Yao-Chieh Hu, Kaize Ding, Han Liu

ICLRW 2025 Statistical Foundations of Conditional Diffusion Transformers Jerry Yao-Chieh Hu, Weimin Wu, Yi-Chen Lee, Yu-Chao Huang, Minshuo Chen, Han Liu

ICML 2024 BiSHop: Bi-Directional Cellular Learning for Tabular Data with Generalized Sparse Modern Hopfield Model Chenwei Xu, Yu-Chao Huang, Jerry Yao-Chieh Hu, Weijian Li, Ammar Gilani, Hsi-Sheng Goan, Han Liu

ICMLW 2024 Fast Adaptation and Robust Quantization of Multi-Modal Foundation Models from Associative Memory: A Case Study in SpeechLM Shang Wu, Yen-Ju Lu, Haozheng Luo, Jerry Yao-Chieh Hu, Jiayi Wang, Najim Dehak, Jesus Villalba, Han Liu

ICML 2024 On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis Jerry Yao-Chieh Hu, Thomas Lin, Zhao Song, Han Liu

NeurIPS 2024 On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs) Jerry Yao-Chieh Hu, Weimin Wu, Zhuoru Li, Sophia Pi, Zhao Song, Han Liu

ICMLW 2024 OutEffHop: A Principled Outlier-Efficient Attention Layer from Dense Associative Memory Models Haozheng Luo, Jerry Yao-Chieh Hu, Pei-Hsuan Chang, Hong-Yu Chen, Weijian Li, Wei-Po Wang, Han Liu

ICML 2024 Outlier-Efficient Hopfield Layers for Large Transformer-Based Models Jerry Yao-Chieh Hu, Pei-Hsuan Chang, Haozheng Luo, Hong-Yu Chen, Weijian Li, Wei-Po Wang, Han Liu

NeurIPS 2024 Provably Optimal Memory Capacity for Modern Hopfield Models: Transformer-Compatible Dense Associative Memories as Spherical Codes Jerry Yao-Chieh Hu, Dennis Wu, Han Liu

ICLR 2024 STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Prediction Dennis Wu, Jerry Yao-Chieh Hu, Weijian Li, Bo-Yu Chen, Han Liu

ICML 2024 Uniform Memory Retrieval with Larger Capacity for Modern Hopfield Models Dennis Wu, Jerry Yao-Chieh Hu, Teng-Yun Hsiao, Han Liu

ICML 2023 Feature Programming for Multivariate Time Series Prediction Alex Daniel Reneau, Jerry Yao-Chieh Hu, Ammar Gilani, Han Liu

AAAI 2023 Ising-Traffic: Using Ising Machine Learning to Predict Traffic Congestion Under Uncertainty Zhenyu Pan, Anshujit Sharma, Jerry Yao-Chieh Hu, Zhuo Liu, Ang Li, Han Liu, Michael C. Huang, Tong Geng

NeurIPS 2023 On Sparse Modern Hopfield Model Jerry Yao-Chieh Hu, Donglin Yang, Dennis Wu, Chenwei Xu, Bo-Yu Chen, Han Liu