Jiaxiang Wu

According to our database, Jiaxiang Wu authored at least 54 papers between 2013 and 2024.

Collaborative distances:

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

2024

Multi-Scale Attention Flow for Probabilistic Time Series Forecasting.

Shibo Feng, Chunyan Miao, Ke Xu, Jiaxiang Wu, Pengcheng Wu, Yang Zhang, Peilin Zhao

IEEE Trans. Knowl. Data Eng., May, 2024

Uncertainty-Calibrated Test-Time Model Adaptation without Forgetting.

Mingkui Tan, Guohao Chen, Jiaxiang Wu, Yifan Zhang, Yaofo Chen, Peilin Zhao, Shuaicheng Niu

CoRR, 2024

MorphGrower: A Synchronized Layer-by-layer Growing Approach for Plausible Neuronal Morphology Generation.

Nianzu Yang, Kaipeng Zeng, Haotian Lu, Yexin Wu, Zexin Yuan, Danni Chen, Shengdian Jiang, Jiaxiang Wu, Yimin Wang, Junchi Yan

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

EBMDock: Neural Probabilistic Protein-Protein Docking via a Differentiable Energy Model.

Huaijin Wu, Wei Liu, Yatao Bian, Jiaxiang Wu, Nianzu Yang, Junchi Yan

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

RPTQ: Reorder-based Post-training Quantization for Large Language Models.

Zhihang Yuan, Lin Niu, Jiawei Liu, Wenyu Liu, Xinggang Wang, Yuzhang Shang, Guangyu Sun, Qiang Wu, Jiaxiang Wu, Bingzhe Wu

CoRR, 2023

Benchmarking the Reliability of Post-training Quantization: a Particular Focus on Worst-case Performance.

Zhihang Yuan, Jiawei Liu, Jiaxiang Wu, Dawei Yang, Qiang Wu, Guangyu Sun, Wenyu Liu, Xinggang Wang, Bingzhe Wu

CoRR, 2023

Anime Character Identification and Tag Prediction by Multimodality Modeling: Dataset and Model.

Fan Yi, Jiaxiang Wu, Minyi Zhao, Shuigeng Zhou

Proceedings of the International Joint Conference on Neural Networks, 2023

Towards Stable Test-time Adaptation in Dynamic Wild World.

Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang, Zhiquan Wen, Yaofo Chen, Peilin Zhao, Mingkui Tan

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Privacy-Preserving Face Recognition Using Random Frequency Components.

Yuxi Mi, Yuge Huang, Jiazhen Ji, Minyi Zhao, Jiaxiang Wu, Xingkun Xu, Shouhong Ding, Shuigeng Zhou

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

PsyCoT: Psychological Questionnaire as Powerful Chain-of-Thought for Personality Detection.

Tao Yang, Tianyuan Shi, Fanqi Wan, Xiaojun Quan, Qifan Wang, Bingzhe Wu, Jiaxiang Wu

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery - a Focus on Affinity Prediction Problems with Noise Annotations.

Yuanfeng Ji, Lu Zhang, Jiaxiang Wu, Bingzhe Wu, Lanqing Li, Long-Kai Huang, Tingyang Xu, Yu Rong, Jie Ren, Ding Xue, Houtim Lai, Wei Liu, Junzhou Huang, Shuigeng Zhou, Ping Luo, Peilin Zhao, Yatao Bian

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Deep Network Quantization via Error Compensation.

Hanyu Peng, Jiaxiang Wu, Zhiwei Zhang, Shifeng Chen, Hai-Tao Zhang

IEEE Trans. Neural Networks Learn. Syst., 2022

Boost Test-Time Performance with Closed-Loop Inference.

Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang, Guanghui Xu, Haokun Li, Peilin Zhao, Junzhou Huang, Yaowei Wang, Mingkui Tan

CoRR, 2022

DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery - A Focus on Affinity Prediction Problems with Noise Annotations.

Yuanfeng Ji, Lu Zhang, Jiaxiang Wu, Bingzhe Wu, Long-Kai Huang, Tingyang Xu, Yu Rong, Lanqing Li, Jie Ren, Ding Xue, Houtim Lai, Shaoyong Xu, Jing Feng, Wei Liu, Ping Luo, Shuigeng Zhou, Junzhou Huang, Peilin Zhao, Yatao Bian

CoRR, 2022

Efficient Test-Time Model Adaptation without Forgetting.

Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang, Yaofo Chen, Shijian Zheng, Peilin Zhao, Mingkui Tan

Proceedings of the International Conference on Machine Learning, 2022

Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning.

Yatao Bian, Yu Rong, Tingyang Xu, Jiaxiang Wu, Andreas Krause, Junzhou Huang

Proceedings of the Tenth International Conference on Learning Representations, 2022

Self-Supervised Pre-training for Protein Embeddings Using Tertiary Structures.

Yuzhi Guo, Jiaxiang Wu, Hehuan Ma, Junzhou Huang

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

GNN-Retro: Retrosynthetic Planning with Graph Neural Networks.

Peng Han, Peilin Zhao, Chan Lu, Junzhou Huang, Jiaxiang Wu, Shuo Shang, Bin Yao, Xiangliang Zhang

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Disturbance-immune weight sharing for neural architecture search.

Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang, Yong Guo, Peilin Zhao, Junzhou Huang, Mingkui Tan

Neural Networks, 2021

EPTool: A New Enhancing PSSM Tool for Protein Secondary Structure Prediction.

Yuzhi Guo, Jiaxiang Wu, Hehuan Ma, Sheng Wang, Junzhou Huang

J. Comput. Biol., 2021

Comprehensive Study on Enhancing Low-Quality Position-Specific Scoring Matrix with Deep Learning for Accurate Protein Structure Property Prediction: Using Bagging Multiple Sequence Alignment Learning.

Yuzhi Guo, Jiaxiang Wu, Hehuan Ma, Sheng Wang, Junzhou Huang

J. Comput. Biol., 2021

Real-Time Semantic Segmentation via Auto Depth, Downsampling Joint Decision and Feature Aggregation.

Peng Sun, Jiaxiang Wu, Songyuan Li, Peiwen Lin, Junzhou Huang, Xi Li

Int. J. Comput. Vis., 2021

Energy-Based Learning for Cooperative Games, with Applications to Feature/Data/Model Valuations.

Yatao Bian, Yu Rong, Tingyang Xu, Jiaxiang Wu, Andreas Krause, Junzhou Huang

CoRR, 2021

EBM-Fold: Fully-Differentiable Protein Folding Powered by Energy-based Models.

Jiaxiang Wu, Shitong Luo, Tao Shen, Haidong Lan, Sheng Wang, Junzhou Huang

CoRR, 2021

tFold-TR: Combining Deep Learning Enhanced Hybrid Potential Energy for Template-Based Modelling Structure Refinement.

Liangzhen Zheng, Haidong Lan, Tao Shen, Jiaxiang Wu, Sheng Wang, Wei Liu, Junzhou Huang

CoRR, 2021

Federated Face Recognition.

Fan Bai, Jiaxiang Wu, Pengcheng Shen, Shaoxin Li, Shuigeng Zhou

CoRR, 2021

AdaXpert: Adapting Neural Architecture for Growing Data.

Shuaicheng Niu, Jiaxiang Wu, Guanghui Xu, Yifan Zhang, Yong Guo, Peilin Zhao, Peng Wang, Mingkui Tan

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

PSSM-Distil: Protein Secondary Structure Prediction (PSSP) on Low-Quality PSSM by Knowledge Distillation with Contrastive Learning.

Qin Wang, Boyuan Wang, Zhenlei Xu, Jiaxiang Wu, Peilin Zhao, Zhen Li, Sheng Wang, Junzhou Huang, Shuguang Cui

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Bayesian Automatic Model Compression.

Jiaxing Wang, Haoli Bai, Jiaxiang Wu, Jian Cheng

IEEE J. Sel. Top. Signal Process., 2020

Bagging MSA Learning: Enhancing Low-Quality PSSM with Deep Learning for Accurate Protein Structure Property Prediction.

Yuzhi Guo, Jiaxiang Wu, Hehuan Ma, Sheng Wang, Junzhou Huang

Proceedings of the Research in Computational Molecular Biology, 2020

Revisiting Parameter Sharing for Automatic Neural Channel Number Search.

Jiaxing Wang, Haoli Bai, Jiaxiang Wu, Xupeng Shi, Junzhou Huang, Irwin King, Michael R. Lyu, Jian Cheng

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

WeightAln: Weighted Homologous Alignment for Protein Structure Property Prediction.

Yuzhi Guo, Jiaxiang Wu, Hehuan Ma, Jinyu Yang, Xinliang Zhu, Junzhou Huang

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

Protein Ensemble Learning with Atrous Spatial Pyramid Networks for Secondary Structure Prediction.

Yuzhi Guo, Jiaxiang Wu, Hehuan Ma, Sheng Wang, Junzhou Huang

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

M-NAS: Meta Neural Architecture Search.

Jiaxing Wang, Jiaxiang Wu, Haoli Bai, Jian Cheng

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

Few Shot Network Compression via Cross Distillation.

Haoli Bai, Jiaxiang Wu, Irwin King, Michael R. Lyu

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

2019

Double Quantization for Communication-Efficient Distributed Optimization.

Yue Yu, Jiaxiang Wu, Longbo Huang

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Collaborative Channel Pruning for Deep Networks.

Hanyu Peng, Jiaxiang Wu, Shifeng Chen, Junzhou Huang

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

Exploring Fast and Communication-Efficient Algorithms in Large-Scale Distributed Networks.

Yue Yu, Jiaxiang Wu, Junzhou Huang

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

An Efficient Approach to Informative Feature Extraction from Multimodal Data.

Lichen Wang, Jiaxiang Wu, Shao-Lun Huang, Lizhong Zheng, Xiangxiang Xu, Lin Zhang, Junzhou Huang

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Quantized CNN: A Unified Approach to Accelerate and Compress Convolutional Networks.

Jian Cheng, Jiaxiang Wu, Cong Leng, Yuhang Wang, Qinghao Hu

IEEE Trans. Neural Networks Learn. Syst., 2018

Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization.

Jiaxiang Wu, Weidong Huang, Junzhou Huang, Tong Zhang

Proceedings of the 35th International Conference on Machine Learning, 2018

Core-set based product quantization for large-scale multimedia search.

Tianli Zhao, Yanshu Jiang, Jiaxiang Wu, Jian Cheng

Proceedings of the 10th International Conference on Internet Multimedia Computing and Service, 2018

2017

Pseudo Label based Unsupervised Deep Discriminative Hashing for Image Retrieval.

Qinghao Hu, Jiaxiang Wu, Jian Cheng, Lifang Wu, Hanqing Lu

Proceedings of the 2017 ACM on Multimedia Conference, 2017

Fast K-means for Large Scale Clustering.

Qinghao Hu, Jiaxiang Wu, Lu Bai, Yifan Zhang, Jian Cheng

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

Bayesian Co-Boosting for Multi-modal Gesture Recognition.

Jiaxiang Wu, Jian Cheng

Proceedings of the Gesture Recognition, 2017

2016

Quantized Convolutional Neural Networks for Mobile Devices.

Jiaxiang Wu, Cong Leng, Yuhang Wang, Qinghao Hu, Jian Cheng

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

Shoot to Know What: An Application of Deep Networks on Mobile Devices.

Jiaxiang Wu, Qinghao Hu, Cong Leng, Jian Cheng

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Learning Deep Features For MSR-bing Information Retrieval Challenge.

Qiang Song, Sixie Yu, Cong Leng, Jiaxiang Wu, Qinghao Hu, Jian Cheng

Proceedings of the 23rd Annual ACM Conference on Multimedia Conference, MM '15, Brisbane, Australia, October 26, 2015

Hashing for Distributed Data.

Cong Leng, Jiaxiang Wu, Jian Cheng, Xi Zhang, Hanqing Lu

Proceedings of the 32nd International Conference on Machine Learning, 2015

Online sketching hashing.

Cong Leng, Jiaxiang Wu, Jian Cheng, Xiao Bai, Hanqing Lu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014

Bayesian co-boosting for multi-modal gesture recognition.

Jiaxiang Wu, Jian Cheng

J. Mach. Learn. Res., 2014

Fast and Accurate Image Matching with Cascade Hashing for 3D Reconstruction.

Jian Cheng, Cong Leng, Jiaxiang Wu, Hainan Cui, Hanqing Lu

Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

Supervised Hashing with Soft Constraints.

Cong Leng, Jian Cheng, Jiaxiang Wu, Xi Zhang, Hanqing Lu

Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014

2013

Fusing multi-modal features for gesture recognition.

Jiaxiang Wu, Jian Cheng, Chaoyang Zhao, Hanqing Lu

Proceedings of the 2013 International Conference on Multimodal Interaction, 2013