Kavli Affiliate: Xiang Zhang | First 5 Authors: Huili Cai, Xiang Zhang, Xiaofeng Liu, , | Summary: Time series classification is a critical task in various domains, such as finance, healthcare, and sensor data analysis. Unsupervised contrastive learning has garnered significant interest in learning effective representations from time series data with limited labels. The prevalent […]
Kavli Affiliate: Feng Wang | First 5 Authors: Yoseob Yoon, Zheyu Lu, Can Uzundal, Ruishi Qi, Wenyu Zhao | Summary: Phononic engineering at GHz frequencies form the foundation of microwave acoustic filters, high-speed acousto-optic modulators, and quantum transducers. THz phononic engineering could lead to acoustic filters and modulators at higher bandwidth and speed, as well […]
Kavli Affiliate: Feng Wang | First 5 Authors: Yoseob Yoon, Zheyu Lu, Can Uzundal, Ruishi Qi, Wenyu Zhao | Summary: Phononic engineering at gigahertz (GHz) frequencies form the foundation of microwave acoustic filters, acousto-optic modulators, and quantum transducers. Terahertz (THz) phononic engineering could lead to acoustic filters and modulators at higher bandwidth and speed, as […]
Kavli Affiliate: Xiang Zhang | First 5 Authors: Minhua Lin, Teng Xiao, Enyan Dai, Xiang Zhang, Suhang Wang | Summary: Graph Contrastive Learning (GCL) has emerged as a popular unsupervised graph representation learning method. However, it has been shown that GCL is vulnerable to adversarial attacks on both the graph structure and node attributes. Although […]
Kavli Affiliate: Feng Wang | First 5 Authors: Guoyizhe Wei, Feng Wang, Anshul Shah, Rama Chellappa, | Summary: Federated learning is a distributed machine learning paradigm that allows multiple clients to collaboratively train a shared model with their local data. Nonetheless, conventional federated learning algorithms often struggle to generalize well due to the ubiquitous domain […]
Kavli Affiliate: Feng Wang | First 5 Authors: Guoyizhe Wei, Feng Wang, Anshul Shah, Rama Chellappa, | Summary: Federated learning is a distributed machine learning paradigm that allows multiple clients to collaboratively train a shared model with their local data. Nonetheless, conventional federated learning algorithms often struggle to generalize well due to the ubiquitous domain […]
Kavli Affiliate: Feng Wang | First 5 Authors: Guoyizhe Wei, Feng Wang, Anshul Shah, Rama Chellappa, | Summary: Federated learning is a distributed machine learning paradigm that allows multiple clients to collaboratively train a shared model with their local data. Nonetheless, conventional federated learning algorithms often struggle to generalize well due to the ubiquitous domain […]
Kavli Affiliate: Feng Wang | First 5 Authors: Guoyizhe Wei, Feng Wang, Anshul Shah, Rama Chellappa, | Summary: Prompt learning has recently become a very efficient transfer learning paradigm for Contrastive Language Image Pretraining (CLIP) models. Compared with fine-tuning the entire encoder, prompt learning can obtain highly competitive results by optimizing only a small number […]
Kavli Affiliate: Kristin A. Persson | First 5 Authors: Guy C. Moore, Matthew K. Horton, Kristin A. Persson, , | Summary: We propose and implement a novel hybrid meta-heuristic optimization algorithm for the identification of non-collinear global ground-states in magnetic systems. The inputs to this optimization scheme are directly from non-collinear density functional theory (DFT), […]
Kavli Affiliate: Feng Wang | First 5 Authors: Chuntian Cao, Matthew R. Carbone, Cem Komurcuoglu, Jagriti S. Shekhawat, Kerry Sun | Summary: Electrochemical degradation of solid electrolytes is a major roadblock in the development of solid-state batteries, and the formed solid-solid interphase (SSI) plays a key role in the performance of solid-state batteries. In this […]