(26,27) DKL combines a GP with a deep neural network, leveraging the ... Recent advancements in machine learning (ML), particularly neural networks, have brought about significant progress in this ...

A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions ...

Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization ...

Researchers from Skoltech and AIRI Institute have shown how machine learning can speed up the development of new materials ...

Understanding neural network dynamics is a cornerstone of systems neuroscience, bridging the gap between biological neural networks and artificial neural ...

This is a potentially valuable modeling study on sequence generation in the hippocampus in a variety of behavioral contexts. While the scope of the model is ambitious, its presentation is incomplete ...

Teaching AI to explore its surroundings is a bit like teaching a robot to find treasure in a vast maze—it needs to try different paths, but some lead nowhere. In many real-world challenges, like ...

Abstract: In process industries, the scarcity of data highlights ... Therefore, we propose a multidomain graph meta-learning network (MDGML) to enable knowledge transfer and enhance information ...