by instadatahelp | Sep 2, 2023 | AI Blogs
F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning Wenhao Li, Bo Jin, Xiangfeng Wang, Junchi Yan, Hongyuan Zha; 24(178):1−75, 2023. Abstract Traditional centralized multi-agent reinforcement learning (MARL)...
![Pooling in Graph Neural Networks using Curvature (arXiv:2308.16516v1 [cs.LG])](https://instadatanews.com/wp-content/uploads/2023/08/arxiv-logo-fb-1080x675.png)
by instadatahelp | Sep 2, 2023 | AI Blogs
The limitations of graph neural networks (GNNs) are often caused by over-squashing and over-smoothing. Over-smoothing erases node differences, while over-squashing hinders information propagation over long distances. These issues stem from the graph structure itself....
by instadatahelp | Sep 2, 2023 | AI Blogs
Inference for Gaussian Processes with Matern Covariogram on Compact Riemannian Manifolds Authors: Didong Li, Wenpin Tang, Sudipto Banerjee; Volume 24(101):1−26, 2023. Abstract Gaussian processes are widely used as versatile modeling and predictive tools in spatial...
by instadatahelp | Sep 2, 2023 | AI Blogs
The field of science is currently facing a crisis in terms of reproducibility. One potential solution that has been proposed is the incorporation of data analysis replications into classrooms. However, the feasibility of this approach and what stakeholders can expect...
by instadatahelp | Sep 2, 2023 | AI Blogs
Variational Inference for Deblending Crowded Starfields Authors: Runjing Liu, Jon D. McAuliffe, Jeffrey Regier; Published in 2023, Volume 24(179):1−36 Abstract In astronomical survey images, it is common for stars and galaxies to visually overlap. Deblending refers to...
