Di Wu

According to our database, Di Wu authored at least 24 papers between 2021 and 2024.

Collaborative distances:

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

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

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

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

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