by instadatahelp | Aug 30, 2023 | AI Blogs
Functional L-Optimality Subsampling for Functional Generalized Linear Models with Massive Data Authors: Hua Liu, Jinhong You, Jiguo Cao; Published in Journal of Machine Learning Research, 24(219):1−41, 2023. Abstract When dealing with massive data, memory and...
![Unified Force-Centric Pre-Training for 3D Molecular Conformations: Harnessing the Force, May the Force be with You (arXiv:2308.14759v1 [physics.chem-ph])](https://instadatanews.com/wp-content/uploads/2023/08/arxiv-logo-fb-1080x675.png)
by instadatahelp | Aug 30, 2023 | AI Blogs
Recent research has demonstrated the potential of utilizing pre-trained models for 3D molecular representation. However, these existing models primarily focus on equilibrium data and neglect off-equilibrium conformations. The main challenge lies in extending these...
by instadatahelp | Aug 30, 2023 | AI Blogs
Bayesian Calibration of Imperfect Computer Models using Physics-Informed Priors Michail Spitieris, Ingelin Steinsland; 24(108):1−39, 2023. Abstract In this paper, we present a computationally efficient data-driven framework for quantifying uncertainty in physical...
by instadatahelp | Aug 30, 2023 | AI Blogs
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning Wei-Fang Sun, Cheng-Kuang Lee, Simon See, Chun-Yi Lee; 24(220):1−32, 2023. Abstract In fully cooperative multi-agent reinforcement learning (MARL) settings, the...
by instadatahelp | Aug 30, 2023 | AI Blogs
Real-time predictive modeling is highly anticipated in the field of industrial artificial intelligence (IAI), where neural networks play a crucial role. To effectively model and save data size for industrial applications, this paper introduces a new randomized learner...
by instadatahelp | Aug 29, 2023 | AI Blogs
The Hyperspherical Geometry of Community Detection: Modularity as a Distance Martijn Gösgens, Remco van der Hofstad, Nelly Litvak; 24(112):1−36, 2023. Abstract This article presents a metric space of clusterings, where clusterings are represented by a binary vector...
