Kavli Affiliate: Xiang Zhang | First 5 Authors: Tianchun Wang, Dongsheng Luo, Wei Cheng, Haifeng Chen, Xiang Zhang | Summary: Graph Neural Networks (GNNs) resurge as a trending research subject owing to their impressive ability to capture representations from graph-structured data. However, the black-box nature of GNNs presents a significant challenge in terms of comprehending […]
Kavli Affiliate: Joel E. Moore | First 5 Authors: Veronika Sunko, Chunxiao Liu, Marc Vila, Ilyoun Na, Yuchen Tang | Summary: Several optical experiments have shown that in magnetic materials the principal axes of response tensors can rotate in a magnetic field. Here we offer a microscopic explanation of this effect, and propose a closely […]
Kavli Affiliate: Feng Wang | First 5 Authors: Meng Lei, Mingchao Cai, Feng Wang, , | Summary: In this work, we introduce an iterative decoupled algorithm designed for addressing the quasi-static multiple-network poroelasticity problem. This problem pertains to the simultaneous modeling of fluid flow and deformations within an elastic porous medium permeated by multiple fluid […]
Kavli Affiliate: Xiang Zhang | First 5 Authors: Yihe Wang, Yu Han, Haishuai Wang, Xiang Zhang, | Summary: Contrastive representation learning is crucial in medical time series analysis as it alleviates dependency on labor-intensive, domain-specific, and scarce expert annotations. However, existing contrastive learning methods primarily focus on one single data level, which fails to fully […]
Kavli Affiliate: Xiang Zhang | First 5 Authors: Yihe Wang, Yu Han, Haishuai Wang, Xiang Zhang, | Summary: Contrastive representation learning is crucial in medical time series analysis as it alleviates dependency on labor-intensive, domain-specific, and scarce expert annotations. However, existing contrastive learning methods primarily focus on one single data level, which fails to fully […]
Kavli Affiliate: Xiang Zhang | First 5 Authors: Yihe Wang, Yu Han, Haishuai Wang, Xiang Zhang, | Summary: Contrastive representation learning is crucial in medical time series analysis as it alleviates dependency on labor-intensive, domain-specific, and scarce expert annotations. However, existing contrastive learning methods primarily focus on one single data level, which fails to fully […]
Kavli Affiliate: Felix Fischer | First 5 Authors: Javier Cembrano, Felix Fischer, Max Klimm, , | Summary: We study functions that produce a ranking of $n$ individuals from $n$ such rankings and are impartial in the sense that the position of an individual in the output ranking does not depend on the input ranking submitted […]
Kavli Affiliate: Felix Fischer | First 5 Authors: Javier Cembrano, Felix Fischer, Max Klimm, , | Summary: We study functions that produce a ranking of $n$ individuals from $n$ such rankings and are impartial in the sense that the position of an individual in the output ranking does not depend on the input ranking submitted […]
Kavli Affiliate: Xiang Zhang | First 5 Authors: Xiang Zhang, Senyu Li, Zijun Wu, Ning Shi, | Summary: Recent advancements in multimodal techniques open exciting possibilities for models excelling in diverse tasks involving text, audio, and image processing. Models like GPT-4V, blending computer vision and language modeling, excel in complex text and image tasks. Numerous […]
Kavli Affiliate: Xiang Zhang | First 5 Authors: Xiang Zhang, Changhao Wang, Lingfeng Sun, Zheng Wu, Xinghao Zhu | Summary: Learning contact-rich manipulation skills is essential. Such skills require the robots to interact with the environment with feasible manipulation trajectories and suitable compliance control parameters to enable safe and stable contact. However, learning these skills […]