Family of New Binary Transition Metal Nitrides Superconductors

Kavli Affiliate: Bo Gu | First 5 Authors: Zheng-Wei Liao, Xin-Wei Yi, Jing-Yang You, Bo Gu, Gang Su | Summary: Superconductivity in transition metal nitrides (TMNs) has been investigated for a long time, such as zirconium nitride (ZrN) with a superconducting transition temperature Tc of 10 K. Recently, a phase diagram has been revealed in […]


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A Repulsive Force Unit for Garment Collision Handling in Neural Networks

Kavli Affiliate: Yi Zhou | First 5 Authors: Qingyang Tan, Yi Zhou, Tuanfeng Wang, Duygu Ceylan, Xin Sun | Summary: Despite recent success, deep learning-based methods for predicting 3D garment deformation under body motion suffer from interpenetration problems between the garment and the body. To address this problem, we propose a novel collision handling neural […]


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Learning Dynamic Facial Radiance Fields for Few-Shot Talking Head Synthesis

Kavli Affiliate: Zheng Zhu | First 5 Authors: Shuai Shen, Wanhua Li, Zheng Zhu, Yueqi Duan, Jie Zhou | Summary: Talking head synthesis is an emerging technology with wide applications in film dubbing, virtual avatars and online education. Recent NeRF-based methods generate more natural talking videos, as they better capture the 3D structural information of […]


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Extracting Densest Sub-hypergraph with Convex Edge-weight Functions

Kavli Affiliate: Yi Zhou | First 5 Authors: Yi Zhou, Shan Hu, Zimo Sheng, , | Summary: The densest subgraph problem (DSG) aiming at finding an induced subgraph such that the average edge-weights of the subgraph is maximized, is a well-studied problem. However, when the input graph is a hypergraph, the existing notion of DSG […]


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DeTrust-FL: Privacy-Preserving Federated Learning in Decentralized Trust Setting

Kavli Affiliate: Yi Zhou | First 5 Authors: Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, Swanand Kadhe | Summary: Federated learning has emerged as a privacy-preserving machine learning approach where multiple parties can train a single model without sharing their raw training data. Federated learning typically requires the utilization of multi-party computation techniques to […]


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DeTrust-FL: Privacy-Preserving Federated Learning in Decentralized Trust Setting

Kavli Affiliate: Yi Zhou | First 5 Authors: Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, Swanand Kadhe | Summary: Federated learning has emerged as a privacy-preserving machine learning approach where multiple parties can train a single model without sharing their raw training data. Federated learning typically requires the utilization of multi-party computation techniques to […]


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CKD-TransBTS: Clinical Knowledge-Driven Hybrid Transformer with Modality-Correlated Cross-Attention for Brain Tumor Segmentation

Kavli Affiliate: Biao Huang | First 5 Authors: Jianwei Lin, Jiatai Lin, Cheng Lu, Hao Chen, Huan Lin | Summary: Brain tumor segmentation (BTS) in magnetic resonance image (MRI) is crucial for brain tumor diagnosis, cancer management and research purposes. With the great success of the ten-year BraTS challenges as well as the advances of […]


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TRIE++: Towards End-to-End Information Extraction from Visually Rich Documents

Kavli Affiliate: Cheng Peng | First 5 Authors: Zhanzhan Cheng, Peng Zhang, Can Li, Qiao Liang, Yunlu Xu | Summary: Recently, automatically extracting information from visually rich documents (e.g., tickets and resumes) has become a hot and vital research topic due to its widespread commercial value. Most existing methods divide this task into two subparts: […]


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Two-stage superconductivity in the Hatsugai-Kohomoto-BCS model

Kavli Affiliate: Yi Zhou | First 5 Authors: Yu Li, Vivek Mishra, Yi Zhou, Fu-Chun Zhang, | Summary: Superconductivity in strongly correlated electrons can emerge out from a normal state that is beyond the Landau’s Fermi liquid paradigm, often dubbed as "non-Fermi liquid". While the theory for non-Fermi liquid is still not yet conclusive, a […]


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