Combinatorics and Computing Weekly Seminar
What AI Can Do in Mathematics and How to Find Sufficient Conditions Using Deep Learning
What AI Can Do in Mathematics and How to Find Sufficient Conditions Using Deep Learning
Farid Aliniaeifard, Shandong University, China
17 JUN 2026
14:00 - 15:00
We first show the capabilities of AI in mathematics by considering different philosophies of mathematics and their relationship with AI. Then we use attribution techniques and exploratory data analysis to give sufficient conditions for a given statement and make conjectures. As a demonstration, we apply this process to Stanley's problem of e-positivity of graphs. Guided by AI, we rediscover that one sufficient condition for a graph to be e-positive is that it is co-triangle-free, and that the number of claws is the most important factor for e-positivity. Based on the most important factors identified in the saliency map analysis of neural networks, we suggest that the classification of e-positive graphs is more likely related to continuous graph invariants rather than discrete ones, and we make some conjectures connecting continuous graph invariants with e-positivity.
This week's talk will be on our Zoom room:
https://us06web.zoom.us/j/86247043799?pwd=KH1lKfYt1rGLzSgKk31MwprllTiOef.1
Meeting ID: 862 4704 3799
Passcode: 362880
Venue: Niavaran, Khosrovshahi Lecture Hall


