The kinematic bimodality: Efficient feedback and cold gas deficiency in slow-rotating galaxies

Kavli Affiliate: Yingjie Peng | First 5 Authors: Bitao Wang, Yingjie Peng, , , | Summary: The bimodality in the stellar spin of low redshift (massive) galaxies, ubiquitously existing at all star formation levels and in diverse environment, suggests that galaxies grow and quench through two diverged evolutionary pathways. For spheroid-dominated galaxies of slow stellar […]


Continue.. The kinematic bimodality: Efficient feedback and cold gas deficiency in slow-rotating galaxies

Long-lived Sterile Neutrino Searches at Future Muon Colliders

Kavli Affiliate: Jia Liu | First 5 Authors: Qi Bi, Jinhui Guo, Jia Liu, Yan Luo, Xiao-Ping Wang | Summary: We explore the potential of studying sterile neutrinos at a future high-energy muon collider, where these particles can generate small active neutrino masses via the seesaw mechanism and exhibit long-lived particle signatures. A Dirac sterile […]


Continue.. Long-lived Sterile Neutrino Searches at Future Muon Colliders

Ctrl-GenAug: Controllable Generative Augmentation for Medical Sequence Classification

Kavli Affiliate: Jia Liu | First 5 Authors: Xinrui Zhou, Yuhao Huang, Haoran Dou, Shijing Chen, Ao Chang | Summary: In the medical field, the limited availability of large-scale datasets and labor-intensive annotation processes hinder the performance of deep models. Diffusion-based generative augmentation approaches present a promising solution to this issue, having been proven effective […]


Continue.. Ctrl-GenAug: Controllable Generative Augmentation for Medical Sequence Classification

Exploring Information-Theoretic Metrics Associated with Neural Collapse in Supervised Training

Kavli Affiliate: Jiansheng Chen | First 5 Authors: Kun Song, Zhiquan Tan, Bochao Zou, Jiansheng Chen, Huimin Ma | Summary: In this paper, we utilize information-theoretic metrics like matrix entropy and mutual information to analyze supervised learning. We explore the information content of data representations and classification head weights and their information interplay during supervised […]


Continue.. Exploring Information-Theoretic Metrics Associated with Neural Collapse in Supervised Training