Summary of Grassnet: State Space Model Meets Graph Neural Network, by Gongpei Zhao et al.
GrassNet: State Space Model Meets Graph Neural Networkby Gongpei Zhao, Tao Wang, Yi Jin, Congyan…
Summary of Linear Combinations Of Latents in Generative Models: Subspaces and Beyond, by Erik Bodin et al.
Linear combinations of latents in generative models: subspaces and beyondby Erik Bodin, Alexandru Stere, Dragos…
Summary of A Mechanistic Interpretation Of Syllogistic Reasoning in Auto-regressive Language Models, by Geonhee Kim et al.
A Mechanistic Interpretation of Syllogistic Reasoning in Auto-Regressive Language Modelsby Geonhee Kim, Marco Valentino, André…
Summary of Radiodiff: An Effective Generative Diffusion Model For Sampling-free Dynamic Radio Map Construction, by Xiucheng Wang and Keda Tao and Nan Cheng and Zhisheng Yin and Zan Li and Yuan Zhang and Xuemin Shen
RadioDiff: An Effective Generative Diffusion Model for Sampling-Free Dynamic Radio Map Constructionby Xiucheng Wang, Keda…
Summary of Generative Dataset Distillation Based on Diffusion Model, by Duo Su et al.
Generative Dataset Distillation Based on Diffusion Modelby Duo Su, Junjie Hou, Guang Li, Ren Togo,…
Summary of Deepdfa: Automata Learning Through Neural Probabilistic Relaxations, by Elena Umili and Roberto Capobianco
DeepDFA: Automata Learning through Neural Probabilistic Relaxationsby Elena Umili, Roberto CapobiancoFirst submitted to arxiv on:…
Summary of A Survey on Secure Decentralized Optimization and Learning, by Changxin Liu et al.
A survey on secure decentralized optimization and learningby Changxin Liu, Nicola Bastianello, Wei Huo, Yang…
Summary of Navigating Uncertainties in Machine Learning For Structural Dynamics: a Comprehensive Review Of Probabilistic and Non-probabilistic Approaches in Forward and Inverse Problems, by Wang-ji Yan (1 and 2) et al.
Navigating Uncertainties in Machine Learning for Structural Dynamics: A Comprehensive Review of Probabilistic and Non-Probabilistic…
Summary of The Power Of Bias: Optimizing Client Selection in Federated Learning with Heterogeneous Differential Privacy, by Jiating Ma et al.
The Power of Bias: Optimizing Client Selection in Federated Learning with Heterogeneous Differential Privacyby Jiating…
Summary of Textcavs: Debugging Vision Models Using Text, by Angus Nicolson et al.
TextCAVs: Debugging vision models using textby Angus Nicolson, Yarin Gal, J. Alison NobleFirst submitted to…