Niu, Di

23 publications

TMLR 2025 FP4DiT: Towards Effective Floating Point Quantization for Diffusion Transformers Ruichen Chen, Keith G. Mills, Di Niu

TMLR 2025 FRAP: Faithful and Realistic Text-to-Image Generation with Adaptive Prompt Weighting Liyao Jiang, Negar Hassanpour, Mohammad Salameh, Mohan Sai Singamsetti, Fengyu Sun, Wei Lu, Di Niu

AAAI 2025 FunEditor: Achieving Complex Image Edits via Function Aggregation with Diffusion Models Mohammadreza Samadi, Fred X. Han, Mohammad Salameh, Hao Wu, Fengyu Sun, Chunhua Zhou, Di Niu

AAAI 2025 PixelMan: Consistent Object Editing with Diffusion Models via Pixel Manipulation and Generation Liyao Jiang, Negar Hassanpour, Mohammad Salameh, Mohammadreza Samadi, Jiao He, Fengyu Sun, Di Niu

AAAI 2025 Qua2SeDiMo: Quantifiable Quantization Sensitivity of Diffusion Models Keith G. Mills, Mohammad Salameh, Ruichen Chen, Negar Hassanpour, Wei Lu, Di Niu

NeurIPS 2025 Re-Ttention: Ultra Sparse Visual Generation via Attention Statistical Reshape Ruichen Chen, Keith G. Mills, Liyao Jiang, Chao Gao, Di Niu

ICLR 2024 Boosting of Thoughts: Trial-and-Error Problem Solving with Large Language Models Sijia Chen, Baochun Li, Di Niu

CVPR 2024 Building Optimal Neural Architectures Using Interpretable Knowledge Keith G. Mills, Fred X. Han, Mohammad Salameh, Shengyao Lu, Chunhua Zhou, Jiao He, Fengyu Sun, Di Niu

TMLR 2024 CascadedGaze: Efficiency in Global Context Extraction for Image Restoration Amirhosein Ghasemabadi, Muhammad Kamran Janjua, Mohammad Salameh, Chunhua Zhou, Fengyu Sun, Di Niu

ICML 2024 EiG-Search: Generating Edge-Induced Subgraphs for GNN Explanation in Linear Time Shengyao Lu, Bang Liu, Keith G Mills, Jiao He, Di Niu

ICLR 2024 GOAt: Explaining Graph Neural Networks via Graph Output Attribution Shengyao Lu, Keith G. Mills, Jiao He, Bang Liu, Di Niu

NeurIPS 2024 Learning Truncated Causal History Model for Video Restoration Amirhosein Ghasemabadi, Muhammad Kamran Janjua, Mohammad Salameh, Di Niu

AAAI 2023 AIO-P: Expanding Neural Performance Predictors Beyond Image Classification Keith G. Mills, Di Niu, Mohammad Salameh, Weichen Qiu, Fred X. Han, Puyuan Liu, Jialin Zhang, Wei Lu, Shangling Jui

NeurIPS 2023 AutoGO: Automated Computation Graph Optimization for Neural Network Evolution Mohammad Salameh, Keith Mills, Negar Hassanpour, Fred Han, Shuting Zhang, Wei Lu, Shangling Jui, Chunhua Zhou, Fengyu Sun, Di Niu

AAAI 2023 GENNAPE: Towards Generalized Neural Architecture Performance Estimators Keith G. Mills, Fred X. Han, Jialin Zhang, Fabian Chudak, Ali Safari Mamaghani, Mohammad Salameh, Wei Lu, Shangling Jui, Di Niu

ICLR 2023 Reparameterization Through Spatial Gradient Scaling Alexander Detkov, Mohammad Salameh, Muhammad Fetrat, Jialin Zhang, Robin Luwei, Shangling Jui, Di Niu

CVPR 2023 Search-mAP-Search: A Frame Selection Paradigm for Action Recognition Mingjun Zhao, Yakun Yu, Xiaoli Wang, Lei Yang, Di Niu

ECCV 2022 LA3: Efficient Label-Aware AutoAugment Mingjun Zhao, Shan Lu, Zixuan Wang, Xiaoli Wang, Di Niu

ICLR 2022 R5: Rule Discovery with Reinforced and Recurrent Relational Reasoning Shengyao Lu, Bang Liu, Keith G. Mills, Shangling Jui, Di Niu

IJCAI 2021 Generative Adversarial Neural Architecture Search Seyed Saeed Changiz Rezaei, Fred X. Han, Di Niu, Mohammad Salameh, Keith G. Mills, Shuo Lian, Wei Lu, Shangling Jui

AAAI 2020 Reinforced Curriculum Learning on Pre-Trained Neural Machine Translation Models Mingjun Zhao, Haijiang Wu, Di Niu, Xiaoli Wang

AAAI 2019 Learning Diffusions Without Timestamps Hao Huang, Qian Yan, Ting Gan, Di Niu, Wei Lu, Yunjun Gao

AAAI 2017 Expectile Matrix Factorization for Skewed Data Analysis Rui Zhu, Di Niu, Linglong Kong, Zongpeng Li