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.

A note on Unapproved Attendance

Due to limited capacity and security reasons, we will not be able to accept and accommodate unapproved drop-ins to the event, so please do not drop by uninvited as you'll be turned away by security. We apologize for the inconvenience and inability to accommodate everyone for this particular session, but please feel free to join us on our next one. Thank you for your understanding.