This repository is a curated list of academic papers exploring the intersection of deep learning and neuroscience, targeting researchers and practitioners in both fields. It aims to provide an overview of recent publications that bridge these disciplines, fostering a deeper understanding of brain-inspired AI and AI-driven neuroscience.

How It Works

The list compiles papers from various sources, including arXiv and major conferences like NeurIPS, ICLR, and Nature. It categorizes publications into "Papers" and "Reviews," with a growing collection of blog posts offering commentary and perspective on the field. The curation focuses on works that investigate how deep learning models can be informed by neuroscience principles or how neuroscience can leverage AI techniques for analysis.

Highlighted Details

• Extensive list of papers from 2014 to 2025 (with some future-dated entries).
• Includes foundational reviews and recent advancements in NeuroAI.
• Covers diverse topics such as language processing, visual recognition, navigation, and learning mechanisms.
• Features contributions from prominent researchers in AI and neuroscience.

Maintenance & Community

The list is maintained through community contributions via pull requests, indicating an active effort to keep it updated. Links to related "awesome" lists are provided for further exploration.

Licensing & Compatibility

The repository itself is likely under a permissive license (e.g., MIT, Apache) as is common for "awesome" lists, but the linked papers are subject to their respective academic publication licenses.

Limitations & Caveats

The README explicitly states that the list represents only a "small subset" of relevant papers due to the rapid growth of both fields. Some entries are dated in the future (2025), suggesting they may be pre-prints or anticipated publications.