Hosted by New York Machine Learning Research Guild (NYMLR)
AI/ML Lecture & Networking @ Intuit
A monthly ML research colloquium by the New York Machine Learning Research Guild — this session in collaboration with our partner, Intuit.
The Mathematical Theory of Deep Learning
Arthur Jacot · Assistant Professor, Courant Institute of Mathematical Sciences, NYU
Topic: TBD
This session is a close-quarters look at that theory, with plenty of room to push back and dig in.
About Arthur
Arthur Jacot is an Assistant Professor at NYU's Courant Institute of Mathematical Sciences. He builds mathematical theory for how deep neural networks learn, and is best known for introducing the Neural Tangent Kernel during a PhD at EPFL with Clément Hongler.
Recent work explains how DNNs act as a computational Occam's razor, finding simple, low-dimensional representations when trained with weight decay:
A proof that wide networks trained with weight decay exhibit neural collapse (ICLR 2025, oral)
An account of how DNNs break the curse of dimensionality through compositionality and symmetry learning (ICLR 2025)
A newer paper framing deep learning as a convex paradigm of computation that minimizes circuit size with ResNets
Arthur's honors include the 2025 AMR Prize in Mathematics of Artificial Intelligence and the 2023 EPFL PhD Thesis Prize.
Who this is for
NY-MLR colloquia are small by design. The room is capped, and we keep it that way so the discussion stays substantive and everyone in it can contribute.
We'd love to see you if you're:
A practitioner working seriously on ML, in industry or in a lab
A researcher or graduate student in ML, mathematics, or an adjacent field
A highly motivated student or self-directed learner of any age or background, with real depth of interest
Sincere interest is enough to belong — that's one of our core principles. What we ask is that you come ready to engage. More on the Guild and our ethos at nymlr.com.
Schedule
5:00 – 5:30 PM · Doors open, arrivals, mingling
5:30 – 6:30 PM · Talk
6:30 – 7:00 PM · Moderated Q&A
7:00 – 8:00 PM · After hours, mingling, wind-down
8:00 PM · Lights out
Venue: Intuit NYC · 51 Astor Pl, New York, NY 10003
Food & drinks
Food and drinks are provided — another reason to claim your seat only if you can make it, and to release it if you can't.
A note on no-shows
Seats are strictly limited by room capacity, and every in-person RSVP takes one from someone else who wanted it.
If you register to attend in person and your plans change, please amend your registration or cancel on Luma. It takes ten seconds and frees the seat.
Registering in person and not showing up without updating your RSVP will forfeit your access to future NY-MLR events. Please mark your attendance mode accurately.
Hosted by New York Machine Learning Research Guild (NYMLR)