Summary of Theoretically Guaranteed Distribution Adaptable Learning, by Chao Xu et al.
Theoretically Guaranteed Distribution Adaptable Learningby Chao Xu, Xijia Tang, Guoqing Liu, Yuhua Qian, Chenping HouFirst…
Summary of Pv-faultnet: Optimized Cnn Architecture to Detect Defects Resulting Efficient Pv Production, by Eiffat E Zaman and Rahima Khanam
PV-faultNet: Optimized CNN Architecture to detect defects resulting efficient PV productionby Eiffat E Zaman, Rahima…
Summary of A Convex Relaxation Approach to Generalization Analysis For Parallel Positively Homogeneous Networks, by Uday Kiran Reddy Tadipatri et al.
A Convex Relaxation Approach to Generalization Analysis for Parallel Positively Homogeneous Networksby Uday Kiran Reddy…
Summary of Generalization and Risk Bounds For Recurrent Neural Networks, by Xuewei Cheng and Ke Huang and Shujie Ma
Generalization and Risk Bounds for Recurrent Neural Networksby Xuewei Cheng, Ke Huang, Shujie MaFirst submitted…
Summary of Dissecting the Failure Of Invariant Learning on Graphs, by Qixun Wang et al.
Dissecting the Failure of Invariant Learning on Graphsby Qixun Wang, Yifei Wang, Yisen Wang, Xianghua…
Summary of Classifier Chain Networks For Multi-label Classification, by Daniel J. W. Touw and Michel Van De Velden
Classifier Chain Networks for Multi-Label Classificationby Daniel J. W. Touw, Michel van de VeldenFirst submitted…
Summary of Learning World Models For Unconstrained Goal Navigation, by Yuanlin Duan et al.
Learning World Models for Unconstrained Goal Navigationby Yuanlin Duan, Wensen Mao, He ZhuFirst submitted to…
Summary of Graph-based Confidence Calibration For Large Language Models, by Yukun Li et al.
Graph-based Confidence Calibration for Large Language Modelsby Yukun Li, Sijia Wang, Lifu Huang, Li-Ping LiuFirst…
Summary of Elu-gcn: Effectively Label-utilizing Graph Convolutional Network, by Jincheng Huang et al.
ELU-GCN: Effectively Label-Utilizing Graph Convolutional Networkby Jincheng Huang, Yujie Mo, Xiaoshuang Shi, Lei Feng, Xiaofeng…
Summary of Grouped Discrete Representation For Object-centric Learning, by Rongzhen Zhao et al.
Grouped Discrete Representation for Object-Centric Learningby Rongzhen Zhao, Vivienne Wang, Juho Kannala, Joni PajarinenFirst submitted…