Hyperparameter Optimization in Binary Communication Networks for Neuromorphic Deployment
Purdue University（普渡大学）；Oak Ridge National Laboratory（橡树岭国家实验室）；Sandia National Laboratories（桑迪亚国家实验室）
Maryam Parsa, Catherine D. Schuman, Prasanna Date, Derek C. Rose, Bill Kay, J. Parker Mitchell, Steven R. Young, Ryan Dellana, William Severa, Thomas E. Potok, Kaushik Roy
Training neural networks for neuromorphic deployment is non-trivial. There have been a variety of approaches proposed to adapt back-propagation or back-propagation-like algorithms appropriate for training. Considering that these networks often have very different performance characteristics than traditional neural networks, it is often unclear how to set either the network topology or the hyperparameters to achieve optimal performance. In this work, we introduce a Bayesian approach for optimizing the hyperparameters of an algorithm for training binary communication networks that can be deployed to neuromorphic hardware. We show that by optimizing the hyperparameters on this algorithm for each dataset, we can achieve improvements in accuracy over the previous state-of-the-art for this algorithm on each dataset (by up to 15 percent). This jump in performance continues to emphasize the potential when converting traditional neural networks to binary communication applicable to neuromorphic hardware.
On-Sensor Data Filtering using Neuromorphic Computing for High Energy Physics Experiments
Oak Ridge National Laboratory（橡树岭国家实验室）；Fermi National Accelerator Laboratory（费米国家加速器实验室）；University of Illinois（伊利诺伊大学）；John Hopkins University（约翰斯·霍普金斯大学）；University of Tennessee（田纳西大学）；University of Kansas（堪萨斯大学）
Neuromorphic Continual Learning for Sequential Deployment of Nuclear Plant Monitoring Systems
University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；University of Texas at El Paso（德克萨斯大学埃尔帕索分校）；National Center for Supercomputing Applications（国家超级计算应用中心）
Energy-Efficient Neuromorphic Computing for Edge AI: A Framework with Adaptive Spiking Neural Networks and Hardware-Aware Optimization
Department of Applied Mathematics and Computer Science (DTU Compute)（应用数学与计算机科学系（DTU计算））；Department of Engineering（工程系）；Department of Computer Engineering（计算机工程系）；Department of Mathematics（数学系）；Department of Computer Systems（计算机系统系）
Towards transferable lightweight neuromorphic computing through a model-free temporal-switch framework
State Key Laboratory of Integrated Chips and Systems（集成芯片与系统国家重点实验室）；Research Institute of Intelligent Complex Systems（智能复杂系统研究院）；Frontier Institute of Chip and System（芯片与系统前沿院）；School of Mathematical Sciences and Shanghai Center for Mathematical Sciences（数学科学学院和上海数学中心）；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institute of Brain Science（医学神经生物学国家重点实验室和教育部脑科学前沿中心，脑科学研究院）
A Realistic Simulation Framework for Analog/Digital Neuromorphic Architectures
Systems Lab, Zernike Institute for Advanced Materials, University of Groningen, Netherlands（格罗宁根大学系统实验室，泽尼克先进材料研究所）；Materials Center, University of Groningen, Netherlands（格罗宁根大学材料中心）；School of Engineering, University of Cádiz, Puerto Real, Cádiz, Spain（卡迪斯大学工程学院）；Institute of Neuroinformatics, University of Zurich（苏黎世大学神经信息研究所）；ETH Zurich, Zurich, Switzerland（苏黎世联邦理工学院）
Modality-Dependent Memory Mechanisms in Cross-Modal Neuromorphic Computing
1 Department of Computer Science, Saint Louis University, St. Louis, MO, USA 2 Luxmuse AI, USA 3 Department of Electrical；Computer Engineering, North Carolina State University, Raleigh, NC, USA 4 Independent Researcher 5 Department of Computer Science, Saint Louis University, St. Louis, MO, USA Email
SpikingJelly: An open-source machine learning infrastructure platform for spike-based intelligence
Peking University（北京大学）；Peng Cheng Laboratory（鹏城实验室）；Shanghai Jiao Tong University（上海交通大学）；Chinese Academy of Sciences（中国科学院）；Centre de Recherche Cerveau et Cognition (CERCO), UMR5549 CNRS - Univ. Toulouse 3（大脑与认知研究中心（CERCO），CNRS UMR5549 - 图卢兹第三大学）；University of Chinese Academy of Sciences（中国科学院大学）
Neuromorphic Cybersecurity with Semi-supervised Lifelong Learning
School of EECS（电子工程与科学学院）；The Pennsylvania State University（宾夕法尼亚州立大学）；Dept. of EECS（电子工程与科学系）；University of Michigan（密歇根大学）；Quantum Ventura, Inc.（Quantum Ventura 公司）；University of Texas at Arlington Research Institute（德克萨斯大学阿灵顿研究 institute）
BrainFuse: a unified infrastructure integrating realistic biological modeling and core AI methodology
Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；Pengcheng Laboratory（鹏城实验室）；The Hong Kong Polytechnic University（香港理工大学）；Tsinghua University（清华大学）；Wuhan University（武汉大学）
Continual Learning with Neuromorphic Computing: Foundations, Methods, and Emerging Applications
Electrical and Communication Engineering Department, United Arab Emirates University (UAEU), Al Ain, United Arab Emirates（阿联酋大学电子与通信工程系）；eBRAIN Lab, New York University (NYU) Abu Dhabi, United Arab Emirates（纽约大学阿布扎赫实验室）；National University of Sciences and Technology (NUST), Pakistan（巴基斯坦国立科学与技术大学）
Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representation
The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；Shenzhen Research Institute of Big Data（深圳大数据研究院）；Peking University（北京大学）；Peng Cheng Laboratory（鹏城实验室）
Energy-Aware Spike Budgeting for Continual Learning in Spiking Neural Networks for Neuromorphic Vision
Dept. of Electrical and Electronics Engineering, University of Liberal Arts Bangladesh（乌拉尔大学 bangladesh 电子与电气工程系）；Dept. of Electrical Engineering, Pennsylvania State University（宾夕法尼亚州立大学电气工程系）
A feedback control optimizer for online and hardware-aware training of Spiking Neural Networks
Institute of Neuroinformatics, University of Zürich and ETH Zürich（神经信息学研究所，苏黎世大学和苏黎世联邦理工学院）；ETH Zürich, Zürich, Switzerland（苏黎世联邦理工学院，苏黎世，瑞士）；Digital Society Initiative, University of Zurich, Switzerland（数字社会倡议，苏黎世大学，瑞士）；AI Center, ETH, Zürich, Switzerland（人工智能中心，苏黎世联邦理工学院，苏黎世，瑞士）
Threshold Modulation for Online Test-Time Adaptation of Spiking Neural Networks
Department of CSE, Southern University of Science and Technology（南方科技大学计算机科学与工程系）；College of Mathematics and Statistics, Chongqing University（重庆大学数学与统计学院）；ACS Laboratory, Huawei Technologies Co., Ltd.（华为技术有限公司ACS实验室）
Auto-Configured Networks for Multi-Scale Multi-Output Time-Series Forecasting
National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Northeastern University（东北大学工业智能与系统优化国家级前沿科学中心）；Innovative Artificial Intelligence Cluster, Digital Future Institute, De Montfort University（德蒙福特大学数字未来研究所创新人工智能集群）；Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University), Ministry of Education（教育部智能工业数据解析与优化重点实验室（东北大学））
Temporal Flexibility in Spiking Neural Networks: Towards Generalization Across Time Steps and Deployment Friendliness
University of Electronic Science and Technology of China（电子科技大学）；Shenzhen Institute for Advanced Study, UESTC（电子科技大学深圳高等研究院）；College of Computing, Georgia Institute of Technology（佐治亚理工学院计算学院）
A Spiking Neural Architecture for Coordinating Arm and Locomotor Control
Centre for Theoretical Neuroscience（理论神经科学中心）；Dept. of Systems Design Engineering, University of Waterloo（滑铁卢大学系统设计工程系）；Applied Brain Research（应用脑研究公司）；Dept. of Nanotechnology Engineering, University of Waterloo（滑铁卢大学纳米技术工程系）；Dept. of Philosophy, University of Waterloo（滑铁卢大学哲学系）
