0
Skip to Content
NSF-Simons AI Institute for Cosmic Origins
The Institute
Internal Resources (Private)
Team
Jobs
News
Programs
Graduate Certificate
Events
Get Involved
NSF-Simons AI Institute for Cosmic Origins
The Institute
Internal Resources (Private)
Team
Jobs
News
Programs
Graduate Certificate
Events
Get Involved
Folder: About
Back
The Institute
Internal Resources (Private)
Team
Jobs
News
Folder: Education
Back
Programs
Graduate Certificate
Events
Get Involved
  • Conference Talks,
• 5/14/25

(Machine) Learning of Dark Matter

In this talk, Dr. Necib discusses multiple different machine learning algorithms that her group has worked on to understand the structure of the Milky Way, and infer properties of the underlying Dark Matter.

Previous

Imaging in Radio Interferometry - What do we measure, model and make decisions about?

Next

Exploring the LLM universe for astronomy research

You Might Also Like

Related Embedded Video Item Thumbnail Towards AI-driven Radio Image Reconstruction
Related Embedded Video Item Thumbnail Compound AI Systems: How Publisher AI Helps Researchers
Related Embedded Video Item Thumbnail Finding Exotic Transients in the Era of Big Data
Related Embedded Video Item Thumbnail Strategies for variance reduction in spectral unmixing
Related Embedded Video Item Thumbnail Cosmological Emulators for High Dimensional Inference

CosmicAI gratefully acknowledges funding from the National Science Foundation under Cooperative Agreement 2421782 and the Simons Foundation award MPS-AI-00010515. To learn more about the NSF AI Institutes program, including information on other AI Institutes, please visit https://aiinstitutes.org.