3 papers
astro-ph.SR2026
A statistical study of the environmental age of core-collapse supernovae based on VLT/MUSE integral-field-unit spectroscopy
Qiang Xi, Ning-Chen Sun, Yihan Zhao +13
We aim to understand the progenitor channels of CCSNe via a statistical study of the ages of their environments. We compiled a large and minimally biased sample of 128 CCSNe discov…
cs.LG2025
ShiftAddNet: A Hardware-Inspired Deep Network
Haoran You, Xiaohan Chen, Yongan Zhang +5
Multiplication (e.g., convolution) is arguably a cornerstone of modern deep neural networks (DNNs). However, intensive multiplications cause expensive resource costs that challenge…
cs.LG2025
Drawing Early-Bird Tickets: Towards More Efficient Training of Deep Networks
Haoran You, Chaojian Li, Pengfei Xu +6
(Frankle & Carbin, 2019) shows that there exist winning tickets (small but critical subnetworks) for dense, randomly initialized networks, that can be trained alone to achieve comp…