Summary of Segment Anything Model For Grain Characterization in Hard Drive Design, by Kai Nichols et al.
Segment Anything Model for Grain Characterization in Hard Drive Designby Kai Nichols, Matthew Hauwiller, Nicholas…
Segment Anything Model for Grain Characterization in Hard Drive Designby Kai Nichols, Matthew Hauwiller, Nicholas…
Dynamics of Meta-learning Representation in the Teacher-student Scenarioby Hui Wang, Cho Tung Yip, Bo LiFirst…
PCGRL+: Scaling, Control and Generalization in Reinforcement Learning Level Generatorsby Sam Earle, Zehua Jiang, Julian…
Cell-ontology guided transcriptome foundation modelby Xinyu Yuan, Zhihao Zhan, Zuobai Zhang, Manqi Zhou, Jianan Zhao,…
Multi-Source Knowledge-Based Hybrid Neural Framework for Time Series Representation Learningby Sagar Srinivas Sakhinana, Krishna Sai…
Self-supervised Learning for Geospatial AI: A Surveyby Yile Chen, Weiming Huang, Kaiqi Zhao, Yue Jiang,…
Transformers are Minimax Optimal Nonparametric In-Context Learnersby Juno Kim, Tai Nakamaki, Taiji SuzukiFirst submitted to…
ELDER: Enhancing Lifelong Model Editing with Mixture-of-LoRAby Jiaang Li, Quan Wang, Zhongnan Wang, Yongdong Zhang,…
Towards Aligned Data Removal via Twin Machine Unlearningby Yuyao Sun, Zhenxing Niu, Gang hua, Rong…
Improving Calibration by Relating Focal Loss, Temperature Scaling, and Propernessby Viacheslav Komisarenko, Meelis KullFirst submitted…