Weihao Gao

According to our database, Weihao Gao authored at least 43 papers between 2014 and 2024.

Collaborative distances:

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

2024

A novel attention-based network for single image dehazing.

Weihao Gao, Yongjun Zhang, Huachun Jian

Vis. Comput., August, 2024

Dual-branch feature fusion dehazing network via multispectral channel attention.

Huachun Jian, Yongjun Zhang, Weihao Gao, Bufan Wang, Guomei Wang

Int. J. Mach. Learn. Cybern., July, 2024

Exploiting local detail in single image super-resolution via hypergraph convolution.

Bufan Wang, Yongjun Zhang, Weihao Gao, He Yao, Ruzhong Chen

Multim. Syst., June, 2024

FNeXter: A Multi-Scale Feature Fusion Network Based on ConvNeXt and Transformer for Retinal OCT Fluid Segmentation.

Zhiyuan Niu, Zhuo Deng, Weihao Gao, Shurui Bai, Zheng Gong, Chucheng Chen, Fuju Rong, Fang Li, Lan Ma

Sensors, April, 2024

Multispectral attention-based network for single image deraining.

Weihao Gao, Yongjun Zhang, Huachun Jian

Signal Image Video Process., February, 2024

Sparse representation scheme with enhanced medium pixel intensity for face recognition.

Xuexue Zhang, Yongjun Zhang, Zewei Wang, Wei Long, Weihao Gao, Bob Zhang

CAAI Trans. Intell. Technol., February, 2024

TabKANet: Tabular Data Modelling with Kolmogorov-Arnold Network and Transformer.

Weihao Gao, Zheng Gong, Zhuo Deng, Fuju Rong, Chucheng Chen, Lan Ma

CoRR, 2024

Crystals with Transformers on Graphs, for Prediction of Unconventional Crystal Material Properties and the Benchmark.

Hongyi Wang, Ji Sun, Jinzhe Liang, Li Zhai, Zitian Tang, Zijian Li, Wei Zhai, Xusheng Wang, Weihao Gao, Sheng Gong, Bolong Huang, Hua Zhang

CoRR, 2024

BAMBOO: a predictive and transferable machine learning force field framework for liquid electrolyte development.

Sheng Gong, Yumin Zhang, Zhenliang Mu, Zhichen Pu, Hongyi Wang, Zhiao Yu, Mengyi Chen, Tianze Zheng, Zhi Wang, Lifei Chen, Xiaojie Wu, Shaochen Shi, Weihao Gao, Wen Yan, Liang Xiang

CoRR, 2024

FTSEGNET: A Novel Transformer-Based Fundus Tumor Segmentation Model Guided by Pre-Trained Classification Results.

Zhuo Deng, Zheng Gong, Weihao Gao, Jingyan Yang, Lei Shao, Fang Li, Wenbin Wei, Lan Ma

Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

DBA-PMC: A Mutually Enhancing Dual-Branch Architecture for Pathologic Myopia and Myopic Maculopathy Classification.

Chucheng Chen, Zheng Gong, Zhuo Deng, Weihao Gao, Fang Li, Lan Ma, Lei Shao, Ruiheng Zhang, Wenbin Wei

Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Predicting City Origin-Destination Flow with Generative Pre-training.

Mingwei Zhang, Lizhong Gao, Qiao Wang, Weihao Gao

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2024, 2024

Enhancing LM's Task Adaptability: Powerful Post-training Framework with Reinforcement Learning from Model Feedback.

Fuju Rong, Weihao Gao, Zhuo Deng, Zheng Gong, Chucheng Chen, Wenze Zhang, Zhiyuan Niu, Fang Li, Lan Ma

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2024, 2024

ProTeM: Unifying Protein Function Prediction via Text Matching.

Ming Qin, Xun Li, Yuhao Wang, Zhenping Li, Hongbin Ye, Zongbing Wang, Weihao Gao, Shangsong Liang, Qiang Zhang, Keyan Ding

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2024, 2024

2023

A deraining with detail-recovery network via context aggregation.

Weihao Gao, Yongjun Zhang, Wei Long, Zhongwei Cui

Multim. Syst., October, 2023

OphGLM: Training an Ophthalmology Large Language-and-Vision Assistant based on Instructions and Dialogue.

Weihao Gao, Zhuo Deng, Zhiyuan Niu, Fuju Rong, Chucheng Chen, Zheng Gong, Wenze Zhang, Daimin Xiao, Fang Li, Zhenjie Cao, Zhaoyi Ma, Wenbin Wei, Lan Ma

CoRR, 2023

Machine Learning Force Fields with Data Cost Aware Training.

Alexander Bukharin, Tianyi Liu, Shengjie Wang, Simiao Zuo, Weihao Gao, Wen Yan, Tuo Zhao

Proceedings of the International Conference on Machine Learning, 2023

2022

Supervised Pretraining for Molecular Force Fields and Properties Prediction.

Xiang Gao, Weihao Gao, Wenzhi Xiao, Zhirui Wang, Chong Wang, Liang Xiang

CoRR, 2022

Learning Regularized Positional Encoding for Molecular Prediction.

Xiang Gao, Weihao Gao, Wenzhi Xiao, Zhirui Wang, Chong Wang, Liang Xiang

CoRR, 2022

Learning to Simulate Unseen Physical Systems with Graph Neural Networks.

Ce Yang, Weihao Gao, Di Wu, Chong Wang

CoRR, 2022

PathFlow: A normalizing flow generator that finds transition paths.

Tianyi Liu, Weihao Gao, Zhirui Wang, Chong Wang

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Label Leakage and Protection in Two-party Split Learning.

Oscar Li, Jiankai Sun, Xin Yang, Weihao Gao, Hongyi Zhang, Junyuan Xie, Virginia Smith, Chong Wang

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Population Risk Improvement with Model Compression: An Information-Theoretic Approach.

Yuheng Bu, Weihao Gao, Shaofeng Zou, Venugopal V. Veeravalli

Entropy, 2021

Learning Large-Time-Step Molecular Dynamics with Graph Neural Networks.

Tianze Zheng, Weihao Gao, Chong Wang

CoRR, 2021

Defending against Reconstruction Attack in Vertical Federated Learning.

Jiankai Sun, Yuanshun Yao, Weihao Gao, Junyuan Xie, Chong Wang

CoRR, 2021

Vertical Federated Learning without Revealing Intersection Membership.

Jiankai Sun, Xin Yang, Yuanshun Yao, Aonan Zhang, Weihao Gao, Junyuan Xie, Chong Wang

CoRR, 2021

One Backward from Ten Forward, Subsampling for Large-Scale Deep Learning.

Chaosheng Dong, Xiaojie Jin, Weihao Gao, Yijia Wang, Hongyi Zhang, Xiang Wu, Jianchao Yang, Xiaobing Liu

CoRR, 2021

Learning An End-to-End Structure for Retrieval in Large-Scale Recommendations.

Weihao Gao, Xiangjun Fan, Chong Wang, Jiankai Sun, Kai Jia, Wenzhi Xiao, Ruofan Ding, Xingyan Bin, Hui Yang, Xiaobing Liu

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

Deep Retrieval: An End-to-End Learnable Structure Model for Large-Scale Recommendations.

Weihao Gao, Xiangjun Fan, Jiankai Sun, Kai Jia, Wenzhi Xiao, Chong Wang, Xiaobing Liu

CoRR, 2020

Information-Theoretic Understanding of Population Risk Improvement with Model Compression.

Yuheng Bu, Weihao Gao, Shaofeng Zou, Venugopal V. Veeravalli

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Information theory meets big data: Theory, algorithms and applications to deep learning

Weihao Gao

PhD thesis, 2019

Rate Distortion For Model Compression: From Theory To Practice.

Weihao Gao, Yu-Han Liu, Chong Wang, Sewoong Oh

Proceedings of the 36th International Conference on Machine Learning, 2019

Learning One-hidden-layer Neural Networks under General Input Distributions.

Weihao Gao, Ashok Vardhan Makkuva, Sewoong Oh, Pramod Viswanath

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Demystifying Fixed k-Nearest Neighbor Information Estimators.

Weihao Gao, Sewoong Oh, Pramod Viswanath

IEEE Trans. Inf. Theory, 2018

Breaking the Bandwidth Barrier: Geometrical Adaptive Entropy Estimation.

Weihao Gao, Sewoong Oh, Pramod Viswanath

IEEE Trans. Inf. Theory, 2018

Rate Distortion For Model Compression: From Theory To Practice.

Weihao Gao, Chong Wang, Sewoong Oh

CoRR, 2018

The Nearest Neighbor Information Estimator is Adaptively Near Minimax Rate-Optimal.

Jiantao Jiao, Weihao Gao, Yanjun Han

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Discovering Potential Correlations via Hypercontractivity.

Hyeji Kim, Weihao Gao, Sreeram Kannan, Sewoong Oh, Pramod Viswanath

Entropy, 2017

Estimating Mutual Information for Discrete-Continuous Mixtures.

Weihao Gao, Sreeram Kannan, Sewoong Oh, Pramod Viswanath

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Density functional estimators with k-nearest neighbor bandwidths.

Weihao Gao, Sewoong Oh, Pramod Viswanath

Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

2016

Causal Strength via Shannon Capacity: Axioms, Estimators and Applications.

Weihao Gao, Sreeram Kannan, Sewoong Oh, Pramod Viswanath

CoRR, 2016

Conditional Dependence via Shannon Capacity: Axioms, Estimators and Applications.

Weihao Gao, Sreeram Kannan, Sewoong Oh, Pramod Viswanath

Proceedings of the 33nd International Conference on Machine Learning, 2016

2014

On the bit error rate of repeated error-correcting codes.

Weihao Gao, Yury Polyanskiy

Proceedings of the 48th Annual Conference on Information Sciences and Systems, 2014