State-of-health (SOH) estimation is a key step in ensuring the safe and reliable operation of batteries. Due to issues such as varying data distribution and sequence length in different cycles, most existing methods require health feature extraction technique, which can be time-consuming and labor-intensive. GRU can well solve this problem due to the simple structure and superior performance, receiving widespread attentions. However, redundant information still exists within the network and impacts the accuracy of SOH estimation. To address this issue, a new GRU network based on Hilbert-Schmidt Independence Criterion (GRU-HSIC) is proposed. First, a zero masking network is used to transform all battery data measured with varying lengths every cycle into sequences of the same length, while still retaining information about the original data size in each cycle. Second, the Hilbert-Schmidt Independence Criterion (HSIC) bottleneck, which evolved from Information Bottleneck (IB) theory, is extended to GRU to compress the information from hidden layers. To evaluate the proposed method, we conducted experiments on datasets from the Center for Advanced Life Cycle Engineering (CALCE) of the University of Maryland and NASA Ames Prognostics Center of Excellence. Experimental results demonstrate that our model achieves higher accuracy than other recurrent models.
Skeleton-based Action Recognition with Non-linear Dependency Modeling and Hilbert-Schmidt Independence Criterion
College of Computer Science and Technology, Jilin University（吉林大学计算机科学与技术学院）；Public Computer Education and Research Center, Jilin University（吉林大学公共计算机教育与研究中心）
Institute for Program Structures and Data Organization, Karlsruhe Institute of Technology（卡尔斯鲁厄理工学院程序结构与数据组织研究所）；Department of Statistics, London School of Economics（伦敦政治经济学院统计系）
Achieving Hilbert-Schmidt Independence Under Rényi Differential Privacy for Fair and Private Data Generation
Department of Mathematics and Computer Science University of Southern Denmark（丹麦南部大学数学与计算机科学系）；Department of Mathematics and Computer Science Freie Universität Berlin（柏林自由大学数学与计算机科学系）；Faculty for Informatik Universität der Bundeswehr München（联邦国防军大学慕尼黑信息学院）
Tiangong University（天津工业大学）；Beijing University of Posts and Telecommunications（北京邮电大学）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）
Path Independent Equilibrium Models Can Better Exploit Test-Time Computation
University of Toronto（多伦多大学）；Vector Institute（向量研究所）；University of California, Berkeley（加州大学伯克利分校）；Stanford University（斯坦福大学）；Google Research（谷歌研究院）；Carnegie Mellon University（卡内基梅隆大学）；Bosch Center for AI（博世人工智能中心）；Princeton University（普林斯顿大学）
The Minimax Rate of HSIC Estimation for Translation-Invariant Kernels
Institute for Program Structures and Data Organization（程序结构与数据组织研究所）；Karlsruhe Institute of Technology（卡尔斯鲁厄理工学院）；Department of Statistics（统计系）；London School of Economics（伦敦政治经济学院）
Designing A Clinically Applicable Deep Recurrent Model to Identify Neuropsychiatric Symptoms in People Living with Dementia Using In-Home Monitoring Data
Imperial College of London（伦敦帝国理工学院）；Imperial College London（伦敦帝国理工学院）；University of Surrey（萨里大学）
Diversity-enhancing Generative Network for Few-shot Hypothesis Adaptation
Hong Kong Baptist University（香港浸会大学）；The University of Melbourne（墨尔本大学）；RIKEN（理化学研究所）；Tianjin Artificial Intelligence Innovation Center（天津人工智能创新中心）；Mohamed bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学）；The University of Sydney（悉尼大学）；The University of Tokyo（东京大学）
Bipartite Graph Variational Auto-Encoder with Fair Latent Representation to Account for Sampling Bias in Ecological Networks
agroparistech（巴黎农业学院）；MNHN, CNRS, SU（法国国家自然博物馆、国家科学研究中心、苏弗尔（SU））；Sorbonne Université, CNRS, IRD, INRAE, Université Paris Est Créteil, Université Paris Cité, Institute of Ecology and Environmental Sciences (iEES-Paris)（索邦大学、国家科学研究中心、国际发展研究所、法国国家农业食品研究咨询中心、巴黎东部大学、巴黎城市大学、生态与环境科学研究所（iEES-巴黎））
Joint SDU-NTU Centre for Artificial Intelligence Research, Shandong University（山东大学-南洋理工大学人工智能联合研究中心,山东大学）；College of Computer and Information Sciences, Southwest University（西南大学计算机与信息科学学院）；School of Software, Shandong University（山东大学软件学院）；CEMSE, King Abdullah University of Science and Technology（计算机、工程与数学科学学院,沙特阿拉伯国王阿卜杜拉科技大学）；Department of Computer Science, George Mason University（乔治梅森大学计算机科学系）
