Summary of Dgdnn: Decoupled Graph Diffusion Neural Network For Stock Movement Prediction, by Zinuo You et al.
DGDNN: Decoupled Graph Diffusion Neural Network for Stock Movement Predictionby Zinuo You, Zijian Shi, Hongbo…
Summary of Probmcl: Simple Probabilistic Contrastive Learning For Multi-label Visual Classification, by Ahmad Sajedi et al.
ProbMCL: Simple Probabilistic Contrastive Learning for Multi-label Visual Classificationby Ahmad Sajedi, Samir Khaki, Yuri A.…
Summary of Motif-aware Riemannian Graph Neural Network with Generative-contrastive Learning, by Li Sun et al.
Motif-aware Riemannian Graph Neural Network with Generative-Contrastive Learningby Li Sun, Zhenhao Huang, Zixi Wang, Feiyang…
Summary of Generalization Properties Of Contrastive World Models, by Kandan Ramakrishnan et al.
Generalization properties of contrastive world modelsby Kandan Ramakrishnan, R. James Cotton, Xaq Pitkow, Andreas S.…
Summary of White-box Transformers Via Sparse Rate Reduction: Compression Is All There Is?, by Yaodong Yu et al.
White-Box Transformers via Sparse Rate Reduction: Compression Is All There Is?by Yaodong Yu, Sam Buchanan,…
Summary of Elucidating and Overcoming the Challenges Of Label Noise in Supervised Contrastive Learning, by Zijun Long et al.
Elucidating and Overcoming the Challenges of Label Noise in Supervised Contrastive Learningby Zijun Long, George…
Summary of Detecting and Learning Out-of-distribution Data in the Open World: Algorithm and Theory, by Yiyou Sun
Detecting and Learning Out-of-Distribution Data in the Open world: Algorithm and Theoryby Yiyou SunFirst submitted…
Summary of Learning For Counterfactual Fairness From Observational Data, by Jing Ma et al.
Learning for Counterfactual Fairness from Observational Databy Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong LiFirst…
Summary of Effective Data Augmentation with Diffusion Models, by Brandon Trabucco et al.
Effective Data Augmentation With Diffusion Modelsby Brandon Trabucco, Kyle Doherty, Max Gurinas, Ruslan SalakhutdinovFirst submitted…