Bingxin Zhou

According to our database, Bingxin Zhou authored at least 24 papers between 2019 and 2024.

Collaborative distances:

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

2024

Two-stream joint matching method based on contrastive learning for few-shot action recognition.

Long Deng, Ziqiang Li, Bingxin Zhou, Zhongming Chen, Ao Li, Yongxin Ge

CoRR, 2024

2023

MathNet: Haar-like wavelet multiresolution analysis for graph representation learning.

Xuebin Zheng, Bingxin Zhou, Ming Li, Yu Guang Wang, Junbin Gao

Knowl. Based Syst., 2023

A Unified View on Neural Message Passing with Opinion Dynamics for Social Networks.

Outongyi Lv, Bingxin Zhou, Jing Wang, Xiang Xiao, Weishu Zhao, Lirong Zheng

CoRR, 2023

LLQL: Logistic Likelihood Q-Learning for Reinforcement Learning.

Outongyi Lv, Bingxin Zhou, Yu Guang Wang

CoRR, 2023

Multi-level Protein Representation Learning for Blind Mutational Effect Prediction.

Yang Tan, Bingxin Zhou, Yuanhong Jiang, Yu Guang Wang, Liang Hong

CoRR, 2023

Accurate and Definite Mutational Effect Prediction with Lightweight Equivariant Graph Neural Networks.

Bingxin Zhou, Outongyi Lv, Kai Yi, Xinye Xiong, Pan Tan, Liang Hong, Yu Guang Wang

CoRR, 2023

Graph Representation Learning for Interactive Biomolecule Systems.

Xinye Xiong, Bingxin Zhou, Yuguang Wang

CoRR, 2023

Framelet Message Passing.

Xinliang Liu, Bingxin Zhou, Chutian Zhang, Yuguang Wang

CoRR, 2023

Robust Graph Representation Learning for Local Corruption Recovery.

Bingxin Zhou, Yuanhong Jiang, Yuguang Wang, Jingwei Liang, Junbin Gao, Shirui Pan, Xiaoqun Zhang

Proceedings of the ACM Web Conference 2023, 2023

Graph Denoising Diffusion for Inverse Protein Folding.

Kai Yi, Bingxin Zhou, Yiqing Shen, Pietro Lió, Yuguang Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

How GNNs Facilitate CNNs in Mining Geometric Information from Large-Scale Medical Images.

Yiqing Shen, Bingxin Zhou, Xinye Xiong, Ruitian Gao, Yu Guang Wang

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

2022

Embedding graphs on Grassmann manifold.

Bingxin Zhou, Xuebin Zheng, Yu Guang Wang, Ming Li, Junbin Gao

Neural Networks, 2022

Decimated Framelet System on Graphs and Fast G-Framelet Transforms.

Xuebin Zheng, Bingxin Zhou, Yu Guang Wang, Xiaosheng Zhuang

J. Mach. Learn. Res., 2022

Graph Neural Network for Local Corruption Recovery.

Bingxin Zhou, Yuanhong Jiang, Yu Guang Wang, Jingwei Liang, Junbin Gao, Shirui Pan, Xiaoqun Zhang

CoRR, 2022

APPROXIMATE EQUIVARIANCE SO(3) NEEDLET CONVOLUTION.

Kai Yi, Jialin Chen, Yu Guang Wang, Bingxin Zhou, Pietro Liò, Yanan Fan, Jan Hamann

Proceedings of the Topological, 2022

Well-Conditioned Spectral Transforms for Dynamic Graph Representation.

Bingxin Zhou, Xinliang Liu, Yuehua Liu, Yunying Huang, Pietro Liò, Yuguang Wang

Proceedings of the Learning on Graphs Conference, 2022

2021

Manifold Optimization-Assisted Gaussian Variational Approximation.

Bingxin Zhou, Junbin Gao, Minh-Ngoc Tran, Richard Gerlach

J. Comput. Graph. Stat., 2021

Spectral Transform Forms Scalable Transformer.

Bingxin Zhou, Xinliang Liu, Yuehua Liu, Yunying Huang, Pietro Liò, Yuguang Wang

CoRR, 2021

Graph Denoising with Framelet Regularizer.

Bingxin Zhou, Ruikun Li, Xuebin Zheng, Yu Guang Wang, Junbin Gao

CoRR, 2021

How Framelets Enhance Graph Neural Networks.

Xuebin Zheng, Bingxin Zhou, Junbin Gao, Yuguang Wang, Pietro Lió, Ming Li, Guido Montúfar

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Graph Neural Networks with Haar Transform-Based Convolution and Pooling: A Complete Guide.

Xuebin Zheng, Bingxin Zhou, Ming Li, Yu Guang Wang, Junbin Gao

CoRR, 2020

ADAMT: A Stochastic Optimization with Trend Correction Scheme.

Bingxin Zhou, Xuebin Zheng, Junbin Gao

CoRR, 2020

On the Trend-corrected Variant of Adaptive Stochastic Optimization Methods.

Bingxin Zhou, Xuebin Zheng, Junbin Gao

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019

Manifold Optimisation Assisted Gaussian Variational Approximation.

Bingxin Zhou, Junbin Gao, Minh-Ngoc Tran, Richard Gerlach

CoRR, 2019