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2020 – today
- 2024
[j8]Bingxin Zhou, Lirong Zheng
, Banghao Wu, Yang Tan, Outongyi Lv, Kai Yi, Guisheng Fan, Liang Hong:
Protein Engineering with Lightweight Graph Denoising Neural Networks. J. Chem. Inf. Model. 64(9): 3650-3661 (2024)- [j7]Yang Tan, Mingchen Li, Bingxin Zhou, Bozitao Zhong, Lirong Zheng, Pan Tan, Ziyi Zhou, Huiqun Yu, Guisheng Fan, Liang Hong:
Simple, Efficient, and Scalable Structure-Aware Adapter Boosts Protein Language Models. J. Chem. Inf. Model. 64(16): 6338-6349 (2024) - [j6]Outongyi Lv, Bingxin Zhou, Lin F. Yang:
Modeling Bellman-error with logistic distribution with applications in reinforcement learning. Neural Networks 177: 106387 (2024) - [j5]Long Deng, Ao Li, Bingxin Zhou, Yongxin Ge:
Two-Stream Temporal Feature Aggregation Based on Clustering for Few-Shot Action Recognition. IEEE Signal Process. Lett. 31: 2435-2439 (2024) - [i23]Long Deng, Ziqiang Li, Bingxin Zhou, Zhongming Chen, Ao Li, Yongxin Ge:
Two-stream joint matching method based on contrastive learning for few-shot action recognition. CoRR abs/2401.04150 (2024) - [i22]Yang Tan, Mingchen Li, Bingxin Zhou, Bozitao Zhong, Lirong Zheng, Pan Tan, Ziyi Zhou, Huiqun Yu, Guisheng Fan, Liang Hong:
Simple, Efficient and Scalable Structure-aware Adapter Boosts Protein Language Models. CoRR abs/2404.14850 (2024) - [i21]Yang Tan, Lirong Zheng, Bozitao Zhong, Liang Hong, Bingxin Zhou:
Protein Representation Learning with Sequence Information Embedding: Does it Always Lead to a Better Performance? CoRR abs/2406.19755 (2024) - [i20]Yutong Hu, Yang Tan, Andi Han, Lirong Zheng, Liang Hong, Bingxin Zhou:
Secondary Structure-Guided Novel Protein Sequence Generation with Latent Graph Diffusion. CoRR abs/2407.07443 (2024) - [i19]Song Li, Yang Tan, Song Ke, Liang Hong, Bingxin Zhou:
Immunogenicity Prediction with Dual Attention Enables Vaccine Target Selection. CoRR abs/2410.02647 (2024) - 2023
- [j4]Xuebin Zheng, Bingxin Zhou, Ming Li, Yu Guang Wang, Junbin Gao:
MathNet: Haar-like wavelet multiresolution analysis for graph representation learning. Knowl. Based Syst. 273: 110609 (2023) - [c7]Yiqing Shen, Bingxin Zhou, Xinye Xiong, Ruitian Gao, Yu Guang Wang:
How GNNs Facilitate CNNs in Mining Geometric Information from Large-Scale Medical Images. BIBM 2023: 2227-2230 - [c6]Kai Yi, Bingxin Zhou, Yiqing Shen, Pietro Lió, Yuguang Wang:
Graph Denoising Diffusion for Inverse Protein Folding. NeurIPS 2023 - [c5]Bingxin Zhou, Yuanhong Jiang, Yuguang Wang, Jingwei Liang, Junbin Gao, Shirui Pan, Xiaoqun Zhang:
Robust Graph Representation Learning for Local Corruption Recovery. WWW 2023: 438-448 - [i18]Xinliang Liu, Bingxin Zhou, Chutian Zhang, Yuguang Wang:
Framelet Message Passing. CoRR abs/2302.14806 (2023) - [i17]Xinye Xiong, Bingxin Zhou, Yuguang Wang:
Graph Representation Learning for Interactive Biomolecule Systems. CoRR abs/2304.02656 (2023) - [i16]Bingxin Zhou, Outongyi Lv, Kai Yi, Xinye Xiong, Pan Tan, Liang Hong, Yu Guang Wang:
Accurate and Definite Mutational Effect Prediction with Lightweight Equivariant Graph Neural Networks. CoRR abs/2304.08299 (2023) - [i15]Yang Tan, Bingxin Zhou, Yuanhong Jiang, Yu Guang Wang, Liang Hong:
Multi-level Protein Representation Learning for Blind Mutational Effect Prediction. CoRR abs/2306.04899 (2023) - [i14]Kai Yi, Bingxin Zhou, Yiqing Shen, Pietro Liò, Yu Guang Wang:
Graph Denoising Diffusion for Inverse Protein Folding. CoRR abs/2306.16819 (2023) - [i13]Outongyi Lv, Bingxin Zhou, Yu Guang Wang:
LLQL: Logistic Likelihood Q-Learning for Reinforcement Learning. CoRR abs/2307.02345 (2023) - [i12]Outongyi Lv, Bingxin Zhou, Jing Wang, Xiang Xiao, Weishu Zhao, Lirong Zheng:
A Unified View on Neural Message Passing with Opinion Dynamics for Social Networks. CoRR abs/2310.01272 (2023) - 2022
- [j3]Xuebin Zheng, Bingxin Zhou, Yu Guang Wang, Xiaosheng Zhuang:
Decimated Framelet System on Graphs and Fast G-Framelet Transforms. J. Mach. Learn. Res. 23: 18:1-18:68 (2022) - [j2]Bingxin Zhou, Xuebin Zheng, Yu Guang Wang, Ming Li, Junbin Gao:
Embedding graphs on Grassmann manifold. Neural Networks 152: 322-331 (2022) - [c4]Bingxin Zhou, Xinliang Liu, Yuehua Liu, Yunying Huang, Pietro Liò, Yuguang Wang:
Well-Conditioned Spectral Transforms for Dynamic Graph Representation. LoG 2022: 12 - [c3]Kai Yi, Jialin Chen, Yu Guang Wang, Bingxin Zhou, Pietro Liò, Yanan Fan, Jan Hamann:
APPROXIMATE EQUIVARIANCE SO(3) NEEDLET CONVOLUTION. TAG-ML 2022: 189-198 - [i11]Bingxin Zhou, Yuanhong Jiang, Yu Guang Wang, Jingwei Liang, Junbin Gao, Shirui Pan, Xiaoqun Zhang:
Graph Neural Network for Local Corruption Recovery. CoRR abs/2202.04936 (2022) - [i10]Bingxin Zhou, Xuebin Zheng, Yu Guang Wang, Ming Li, Junbin Gao:
Embedding Graphs on Grassmann Manifold. CoRR abs/2205.15068 (2022) - [i9]Yiqing Shen, Bingxin Zhou, Xinye Xiong, Ruitian Gao, Yu Guang Wang:
How GNNs Facilitate CNNs in Mining Geometric Information from Large-Scale Medical Images. CoRR abs/2206.07599 (2022) - [i8]Kai Yi, Jialin Chen, Yu Guang Wang, Bingxin Zhou, Pietro Liò, Yanan Fan, Jan Hamann:
Approximate Equivariance SO(3) Needlet Convolution. CoRR abs/2206.10385 (2022) - 2021
- [j1]Bingxin Zhou, Junbin Gao, Minh-Ngoc Tran, Richard Gerlach:
Manifold Optimization-Assisted Gaussian Variational Approximation. J. Comput. Graph. Stat. 30(4): 946-957 (2021) - [c2]Xuebin Zheng, Bingxin Zhou, Junbin Gao, Yuguang Wang, Pietro Lió, Ming Li, Guido Montúfar:
How Framelets Enhance Graph Neural Networks. ICML 2021: 12761-12771 - [i7]Xuebin Zheng, Bingxin Zhou, Junbin Gao, Yu Guang Wang, Pietro Liò, Ming Li, Guido Montúfar:
How Framelets Enhance Graph Neural Networks. CoRR abs/2102.06986 (2021) - [i6]Bingxin Zhou, Ruikun Li, Xuebin Zheng, Yu Guang Wang, Junbin Gao:
Graph Denoising with Framelet Regularizer. CoRR abs/2111.03264 (2021) - [i5]Bingxin Zhou, Xinliang Liu, Yuehua Liu, Yunying Huang, Pietro Liò, Yuguang Wang:
Spectral Transform Forms Scalable Transformer. CoRR abs/2111.07602 (2021) - 2020
- [c1]Bingxin Zhou, Xuebin Zheng, Junbin Gao:
On the Trend-corrected Variant of Adaptive Stochastic Optimization Methods. IJCNN 2020: 1-8 - [i4]Bingxin Zhou, Xuebin Zheng, Junbin Gao:
ADAMT: A Stochastic Optimization with Trend Correction Scheme. CoRR abs/2001.06130 (2020) - [i3]Xuebin Zheng, Bingxin Zhou, Ming Li, Yu Guang Wang, Junbin Gao:
Graph Neural Networks with Haar Transform-Based Convolution and Pooling: A Complete Guide. CoRR abs/2007.11202 (2020) - [i2]Xuebin Zheng, Bingxin Zhou, Yu Guang Wang, Xiaosheng Zhuang:
Decimated Framelet System on Graphs and Fast G-Framelet Transforms. CoRR abs/2012.06922 (2020)
2010 – 2019
- 2019
- [i1]Bingxin Zhou, Junbin Gao, Minh-Ngoc Tran, Richard Gerlach:
Manifold Optimisation Assisted Gaussian Variational Approximation. CoRR abs/1902.03718 (2019)
Coauthor Index
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last updated on 2024-11-08 21:31 CET by the dblp team
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