Identifying Novel Patterns What are the limitations of using neural networks as a tool for scientific discovery

Computational scientist seeking data science and ML/AI engineering positions · Currently, I am a senior undergraduate student at UVM working on my thesis ... a type of universal function approximators that can embed the knowledge of any physical laws that govern a given data-set in the learning process. Apr 28, 2021 ... First, the Information Bottleneck Principle is not the same as bottleneck layers in networks like auto-encoders. These can serve as information ... Jun 23, 2020 ... In this paper we develop a novel mathematical formalism for the modeling of neural information networks endowed with additional structure. Here we employ an information-decomposition framework to investigate neural networks performing cognitive tasks. Our results show that synergy increases as ... Feb 28, 2024 ... Intellectualization, cybersecurity, biometric image, deepfake, information technology, neural networks, detection system, instrumental platform, ... in the upper network level. Moreover, in a slightly different direction, research on multi-task learning neural networks, an approach aiming at internal ... Informational capacity and recall quality in sparsely encoded Hopfield-like neural network: analytical approaches and computer simulation Dec 20, 2024 ... In ecosystems, financial markets, and neural networks, entropy fluctuates as new information reshapes the probability landscape. 4.2 The ... Feb 26, 2021 ... We developed a context-aware graph neural network (GNN) model utilizing the pairwise relationship among participants to investigate the ...