Chen, Jianfei

47 publications

ICLR 2025 COAT: Compressing Optimizer States and Activations for Memory-Efficient FP8 Training Haocheng Xi, Han Cai, Ligeng Zhu, Yao Lu, Kurt Keutzer, Jianfei Chen, Song Han

ICLR 2025 Diffusion Bridge Implicit Models Kaiwen Zheng, Guande He, Jianfei Chen, Fan Bao, Jun Zhu

ICLR 2025 Elucidating the Preconditioning in Consistency Distillation Kaiwen Zheng, Guande He, Jianfei Chen, Fan Bao, Jun Zhu

ICML 2025 FrameBridge: Improving Image-to-Video Generation with Bridge Models Yuji Wang, Zehua Chen, Chen Xiaoyu, Yixiang Wei, Jun Zhu, Jianfei Chen

ICLR 2025 On the Optimization and Generalization of Two-Layer Transformers with Sign Gradient Descent Bingrui Li, Wei Huang, Andi Han, Zhanpeng Zhou, Taiji Suzuki, Jun Zhu, Jianfei Chen

ICML 2025 Oscillation-Reduced MXFP4 Training for Vision Transformers Yuxiang Chen, Haocheng Xi, Jun Zhu, Jianfei Chen

AAAI 2025 Pruning Large Language Models with Semi-Structural Adaptive Sparse Training Weiyu Huang, Yuezhou Hu, Guohao Jian, Jun Zhu, Jianfei Chen

ICLR 2025 ReMoE: Fully Differentiable Mixture-of-Experts with ReLU Routing Ziteng Wang, Jun Zhu, Jianfei Chen

ICLRW 2025 SageAttention2: Efficient Attention with Smoothing Q and Per-Thread Quantization Jintao Zhang, Haofeng Huang, Pengle Zhang, Jia Wei, Jun Zhu, Jianfei Chen

ICML 2025 SageAttention2: Efficient Attention with Thorough Outlier Smoothing and Per-Thread INT4 Quantization Jintao Zhang, Haofeng Huang, Pengle Zhang, Jia Wei, Jun Zhu, Jianfei Chen

NeurIPS 2025 SageAttention3: Microscaling FP4 Attention for Inference and an Exploration of 8-Bit Training Jintao Zhang, Jia Wei, Haoxu Wang, Pengle Zhang, Xiaoming Xu, Haofeng Huang, Kai Jiang, Jianfei Chen, Jun Zhu

ICLR 2025 SageAttention: Accurate 8-Bit Attention for Plug-and-Play Inference Acceleration Jintao Zhang, Jia Wei, Pengle Zhang, Jun Zhu, Jianfei Chen

ICML 2025 SpargeAttention: Accurate and Training-Free Sparse Attention Accelerating Any Model Inference Jintao Zhang, Chendong Xiang, Haofeng Huang, Jia Wei, Haocheng Xi, Jun Zhu, Jianfei Chen

ICLRW 2025 SpargeAttn: Training-Free Sparse Attention Accelerating Any Model Inference Jintao Zhang, Chendong Xiang, Haofeng Huang, Jia Wei, Haocheng Xi, Jun Zhu, Jianfei Chen

ICML 2025 Sparse Video-Gen: Accelerating Video Diffusion Transformers with Spatial-Temporal Sparsity Haocheng Xi, Shuo Yang, Yilong Zhao, Chenfeng Xu, Muyang Li, Xiuyu Li, Yujun Lin, Han Cai, Jintao Zhang, Dacheng Li, Jianfei Chen, Ion Stoica, Kurt Keutzer, Song Han

NeurIPS 2025 Sparse VideoGen2: Accelerate Video Generation with Sparse Attention via Semantic-Aware Permutation Shuo Yang, Haocheng Xi, Yilong Zhao, Muyang Li, Jintao Zhang, Han Cai, Yujun Lin, Xiuyu Li, Chenfeng Xu, Kelly Peng, Jianfei Chen, Song Han, Kurt Keutzer, Ion Stoica

ICCV 2025 Task-Specific Zero-Shot Quantization-Aware Training for Object Detection Changhao Li, Xinrui Chen, Ji Wang, Kang Zhao, Jianfei Chen

ICML 2025 Visual Generation Without Guidance Huayu Chen, Kai Jiang, Kaiwen Zheng, Jianfei Chen, Hang Su, Jun Zhu

ICML 2024 Accelerating Transformer Pre-Training with 2:4 Sparsity Yuezhou Hu, Kang Zhao, Weiyu Huang, Jianfei Chen, Jun Zhu

NeurIPS 2024 C-GAIL: Stabilizing Generative Adversarial Imitation Learning with Control Theory Tianjiao Luo, Tim Pearce, Huayu Chen, Jianfei Chen, Jun Zhu

TMLR 2024 Calibrating Deep Ensemble Through Functional Variational Inference Zhijie Deng, Feng Zhou, Jianfei Chen, Guoqiang Wu, Jun Zhu

NeurIPS 2024 Consistency Diffusion Bridge Models Guande He, Kaiwen Zheng, Jianfei Chen, Fan Bao, Jun Zhu

ICLR 2024 Efficient Backpropagation with Variance Controlled Adaptive Sampling Ziteng Wang, Jianfei Chen, Jun Zhu

ICML 2024 Jetfire: Efficient and Accurate Transformer Pretraining with INT8 Data Flow and Per-Block Quantization Haocheng Xi, Yuxiang Chen, Kang Zhao, Kai Jun Teh, Jianfei Chen, Jun Zhu

NeurIPS 2024 S-STE: Continuous Pruning Function for Efficient 2:4 Sparse Pre-Training Yuezhou Hu, Jun Zhu, Jianfei Chen

ICML 2023 Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning Cheng Lu, Huayu Chen, Jianfei Chen, Hang Su, Chongxuan Li, Jun Zhu

NeurIPS 2023 DPM-Solver-V3: Improved Diffusion ODE Solver with Empirical Model Statistics Kaiwen Zheng, Cheng Lu, Jianfei Chen, Jun Zhu

ICML 2023 Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs Kaiwen Zheng, Cheng Lu, Jianfei Chen, Jun Zhu

NeurIPS 2023 Memory Efficient Optimizers with 4-Bit States Bingrui Li, Jianfei Chen, Jun Zhu

ICLR 2023 Preserving Pre-Trained Features Helps Calibrate Fine-Tuned Language Models Guande He, Jianfei Chen, Jun Zhu

ICML 2023 Stabilizing GANs’ Training with Brownian Motion Controller Tianjiao Luo, Ziyu Zhu, Jianfei Chen, Jun Zhu

NeurIPS 2023 Training Transformers with 4-Bit Integers Haocheng Xi, ChangHao Li, Jianfei Chen, Jun Zhu

NeurIPS 2022 DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu

ICML 2022 Fast Lossless Neural Compression with Integer-Only Discrete Flows Siyu Wang, Jianfei Chen, Chongxuan Li, Jun Zhu, Bo Zhang

ICML 2022 GACT: Activation Compressed Training for Generic Network Architectures Xiaoxuan Liu, Lianmin Zheng, Dequan Wang, Yukuo Cen, Weize Chen, Xu Han, Jianfei Chen, Zhiyuan Liu, Jie Tang, Joey Gonzalez, Michael Mahoney, Alvin Cheung

ICML 2022 Maximum Likelihood Training for Score-Based Diffusion ODEs by High Order Denoising Score Matching Cheng Lu, Kaiwen Zheng, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu

ICML 2021 ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training Jianfei Chen, Lianmin Zheng, Zhewei Yao, Dequan Wang, Ion Stoica, Michael Mahoney, Joseph Gonzalez

ICLR 2021 Implicit Normalizing Flows Cheng Lu, Jianfei Chen, Chongxuan Li, Qiuhao Wang, Jun Zhu

NeurIPS 2020 A Statistical Framework for Low-Bitwidth Training of Deep Neural Networks Jianfei Chen, Yu Gai, Zhewei Yao, Michael W. Mahoney, Joseph E Gonzalez

ICML 2020 VFlow: More Expressive Generative Flows with Variational Data Augmentation Jianfei Chen, Cheng Lu, Biqi Chenli, Jun Zhu, Tian Tian

NeurIPS 2018 Stochastic Expectation Maximization with Variance Reduction Jianfei Chen, Jun Zhu, Yee Whye Teh, Tong Zhang

ICML 2018 Stochastic Training of Graph Convolutional Networks with Variance Reduction Jianfei Chen, Jun Zhu, Le Song

AAAI 2018 Towards Training Probabilistic Topic Models on Neuromorphic Multi-Chip Systems Zihao Xiao, Jianfei Chen, Jun Zhu

NeurIPS 2017 Population Matching Discrepancy and Applications in Deep Learning Jianfei Chen, Chongxuan Li, Yizhong Ru, Jun Zhu

ICML 2014 Bayesian Max-Margin Multi-Task Learning with Data Augmentation Chengtao Li, Jun Zhu, Jianfei Chen

AAAI 2014 Dropout Training for Support Vector Machines Ning Chen, Jun Zhu, Jianfei Chen, Bo Zhang

NeurIPS 2013 Scalable Inference for Logistic-Normal Topic Models Jianfei Chen, Jun Zhu, Zi Wang, Xun Zheng, Bo Zhang