Di Wu

According to our database, Di Wu authored at least 41 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Neuro-BERT: Rethinking Masked Autoencoding for Self-Supervised Neurological Pretraining.

Di Wu, Siyuan Li, Jie Yang, Mohamad Sawan

IEEE J. Biomed. Health Informatics, February, 2026

Rethinking Crystal Symmetry Prediction: A Decoupled Perspective.

Liheng Yu, Zhe Zhao, Xucong Wang, Di Wu, Pengkun Wang

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

Learning Dynamics as Feedback: An Adaptive Entropy Flow Dynamics Framework for Long-tailed Human Action Recognition.

Yuan Dong, Zhe Zhao, Liheng Yu, Di Wu, Pengkun Wang

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

CSDformer: A Conversion Method for Fully Spike-Driven Transformer.

Yuhao Zhang, Chengjun Zhang, Di Wu, Jie Yang, Mohamad Sawan

CoRR, September, 2025

NeuroCLIP: A Multimodal Contrastive Learning Method for rTMS-treated Methamphetamine Addiction Analysis.

Chengkai Wang, Di Wu, Yunsheng Liao, Wenyao Zheng, Ziyi Zeng, Xurong Gao, Hemmings Wu, Zhoule Zhu, Jie Yang, Lihua Zhong, Weiwei Cheng, Yun-Hsuan Chen, Mohamad Sawan

CoRR, July, 2025

Towards Unified Neural Decoding with Brain Functional Network Modeling.

Di Wu, Linghao Bu, Yifei Jia, Lu Cao, Siyuan Li, Siyu Chen, Yueqian Zhou, Sheng Fan, Wenjie Ren, Dengchang Wu, Kang Wang, Yue Zhang, Yuehui Ma, Jie Yang, Mohamad Sawan

CoRR, June, 2025

GenURL: A General Framework for Unsupervised Representation Learning.

Siyuan Li, Zicheng Liu, Zelin Zang, Di Wu, Zhiyuan Chen, Stan Z. Li

IEEE Trans. Neural Networks Learn. Syst., January, 2025

A Resource-Efficient Algorithm-Hardware Co-Design Toward Semi-Supervised Neurological Symptoms Prediction.

Shiqi Zhao, Shanjin Li, Di Wu, Fengshi Tian, Jie Yang, Mohamad Sawan

IEEE Trans. Instrum. Meas., 2025

IIB-DDI: Invariant Information Bottleneck Theory for Out-of-Distribution Drug-Drug Interaction Prediction.

Jiahui Zhang, Shuai Zhang, Xuqiang Li, Di Wu, Sihan Wang, Limin Li, Wenjie Du, Yang Wang

IEEE Trans. Comput. Biol. Bioinform., 2025

Towards Homogeneous Lexical Tone Decoding from Heterogeneous Intracranial Recordings.

Di Wu, Siyuan Li, Chen Feng, Lu Cao, Yue Zhang, Jie Yang, Mohamad Sawan

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Switch EMA: A Free Lunch for Better Flatness and Sharpness.

Siyuan Li, Zicheng Liu, Juanxi Tian, Ge Wang, Zedong Wang, Weiyang Jin, Di Wu, Cheng Tan, Tao Lin, Yang Liu, Baigui Sun, Stan Z. Li

CoRR, 2024

Masked Modeling for Self-supervised Representation Learning on Vision and Beyond.

Siyuan Li, Luyuan Zhang, Zedong Wang, Di Wu, Lirong Wu, Zicheng Liu, Jun Xia, Cheng Tan, Yang Liu, Baigui Sun, Stan Z. Li

CoRR, 2024

MMGNN: A Molecular Merged Graph Neural Network for Explainable Solvation Free Energy Prediction.

Wenjie Du, Shuai Zhang, Di Wu, Jun Xia, Ziyuan Zhao, Junfeng Fang, Yang Wang

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

VQDNA: Unleashing the Power of Vector Quantization for Multi-Species Genomic Sequence Modeling.

Siyuan Li, Zedong Wang, Zicheng Liu, Di Wu, Cheng Tan, Jiangbin Zheng, Yufei Huang, Stan Z. Li

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Exploring Effective Stimulus Encoding via Vision System Modeling for Visual Prostheses.

Chuanqing Wang, Di Wu, Chaoming Fang, Jie Yang, Mohamad Sawan

Proceedings of the Twelfth International Conference on Learning Representations, 2024

MogaNet: Multi-order Gated Aggregation Network.

Siyuan Li, Zedong Wang, Zicheng Liu, Cheng Tan, Haitao Lin, Di Wu, Zhiyuan Chen, Jiangbin Zheng, Stan Z. Li

Proceedings of the Twelfth International Conference on Learning Representations, 2024

XRDMamba: Large-scale Crystal Material Space Group Identification with Selective State Space Model.

Liheng Yu, Pengkun Wang, Zhe Zhao, Zhongchao Yi, Sun Nan, Di Wu, Yang Wang

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

Software-Hardware Co-Design for Energy-Efficient Continuous Health Monitoring via Task-Aware Compression.

Di Wu, Shiqi Zhao, Jie Yang, Mohamad Sawan

IEEE Trans. Biomed. Circuits Syst., April, 2023

Fusing 2D and 3D molecular graphs as unambiguous molecular descriptors for conformational and chiral stereoisomers.

Wenjie Du, Xiaoting Yang, Di Wu, Fenfen Ma, Baicheng Zhang, Chaochao Bao, Yaoyuan Huo, Jun Jiang, Xin Chen, Yang Wang

Briefings Bioinform., January, 2023

Architecture-Agnostic Masked Image Modeling - From ViT back to CNN.

Siyuan Li, Di Wu, Fang Wu, Zelin Zang, Stan Z. Li

Proceedings of the International Conference on Machine Learning, 2023

Task-aware Compression for Wearable Sensor Data.

Di Wu, Jie Yang, Mohamad Sawan

Proceedings of the IEEE Biomedical Circuits and Systems Conference, 2023

Improving efficiency in rationale discovery for Out-of-Distribution molecular representations.

Jiahui Zhang, Jiahe Li, Wenjie Du, Shuai Zhang, Di Wu, Yang Wang

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

2022

Deep manifold embedding of attributed graphs.

Zelin Zang, Siyuan Li, Di Wu, Jianzhu Guo, Yongjie Xu, Stan Z. Li

Neurocomputing, 2022

Efficient Multi-order Gated Aggregation Network.

Siyuan Li, Zedong Wang, Zicheng Liu, Cheng Tan, Haitao Lin, Di Wu, Zhiyuan Chen, Jiangbin Zheng, Stan Z. Li

CoRR, 2022

Transfer Learning on Electromyography (EMG) Tasks: Approaches and Beyond.

Di Wu, Jie Yang, Mohamad Sawan

CoRR, 2022

OpenMixup: Open Mixup Toolbox and Benchmark for Visual Representation Learning.

Siyuan Li, Zedong Wang, Zicheng Liu, Di Wu, Stan Z. Li

CoRR, 2022

DLME: Deep Local-flatness Manifold Embedding.

Zelin Zang, Siyuan Li, Di Wu, Ge Wang, Lei Shang, Baigui Sun, Hao Li, Stan Z. Li

CoRR, 2022

Architecture-Agnostic Masked Image Modeling - From ViT back to CNN.

Siyuan Li, Di Wu, Fang Wu, Zelin Zang, Kai Wang, Lei Shang, Baigui Sun, Hao Li, Stan Z. Li

CoRR, 2022

neuro2vec: Masked Fourier Spectrum Prediction for Neurophysiological Representation Learning.

Di Wu, Siyuan Li, Jie Yang, Mohamad Sawan

CoRR, 2022

Bridging the Gap Between Patient-specific and Patient-independent Seizure Prediction via Knowledge Distillation.

Di Wu, Jie Yang, Mohamad Sawan

CoRR, 2022

Towards Task-aware Signal Compression for Efficient Continuous Health Monitoring.

Di Wu, Jie Yang, Mohamad Sawan

Proceedings of the IEEE International Symposium on Circuits and Systems, 2022

DLME: Deep Local-Flatness Manifold Embedding.

Zelin Zang, Siyuan Li, Di Wu, Ge Wang, Kai Wang, Lei Shang, Baigui Sun, Hao Li, Stan Z. Li

Proceedings of the Computer Vision - ECCV 2022, 2022

AutoMix: Unveiling the Power of Mixup for Stronger Classifiers.

Zicheng Liu, Siyuan Li, Di Wu, Zihan Liu, Zhiyuan Chen, Lirong Wu, Stan Z. Li

Proceedings of the Computer Vision, 2022

Exploring Localization for Self-supervised Fine-grained Contrastive Learning.

Di Wu, Siyuan Li, Zelin Zang, Stan Z. Li

Proceedings of the 33rd British Machine Vision Conference 2022, 2022

A Resource-Efficient and Data-Restricted Training Method Towards Neurological Symptoms Prediction.

Shiqi Zhao, Di Wu, Jie Yang, Mohamad Sawan

Proceedings of the IEEE Biomedical Circuits and Systems Conference, 2022

2021

Boosting Discriminative Visual Representation Learning with Scenario-Agnostic Mixup.

Siyuan Li, Zicheng Liu, Di Wu, Zihan Liu, Stan Z. Li

CoRR, 2021

GenURL: A General Framework for Unsupervised Representation Learning.

Siyuan Li, Zelin Zang, Di Wu, Zhiyuan Chen, Stan Z. Li

CoRR, 2021

C²SP-Net: Joint Compression and Classification Network for Epilepsy Seizure Prediction.

Di Wu, Yi Shi, Ziyu Wang, Jie Yang, Mohamad Sawan

CoRR, 2021

Align Yourself: Self-supervised Pre-training for Fine-grained Recognition via Saliency Alignment.

Di Wu, Siyuan Li, Zelin Zang, Kai Wang, Lei Shang, Baigui Sun, Hao Li, Stan Z. Li

CoRR, 2021

Unsupervised Deep Manifold Attributed Graph Embedding.

Zelin Zang, Siyuan Li, Di Wu, Jianzhu Guo, Yongjie Xu, Stan Z. Li

CoRR, 2021

AutoMix: Unveiling the Power of Mixup.

Zicheng Liu, Siyuan Li, Di Wu, Zhiyuan Chen, Lirong Wu, Jianzhu Guo, Stan Z. Li

CoRR, 2021