Shape the Technology that will Shape your Future
Nagymaros AI Retreat
23 Oct - 1 Nov 2024
This year's theme: Knots
AI for Mathematics
In last year's AI retreat, we had lots of fun applying ML to an interesting maths problem, so this year's retreat will go all in. We will focus entirely on working with mathematical data: knots. Knot theory is an interesting area of mathematics with a lot of interesting structure, but a low barrier to entry. We will look into learning knot invariants, learning to unknot, factorizing composite knots into prime components, and many more.
Representation Learning and Geometric Deep Learning
We will learn about choosing the right, mathematically motivated architectures for the problems involving knots. There are several invariances that can be exploited in creative ways to make the learning problem easier, and the solutions more robust. We will explore concepts like circular convolution, convolutional transformers and more.
Reinforcement Learning
Several problems related to knots can be framed as Markov decision processes: similar to games like chess or go, but instead of a board, the state of the game is a knot, and instead of moves, we have mathematical transformations and operations to work with. This makes these problems an ideal playground to learn reinforcement learning algorithms, such as Monte Carlo tree search, Q-learning, and more.
Sponsorship
This year's event is sponsored by G-Research. Thank you!
Agenda
Wednesday, 23 October
- arrival at Mihály utca
- 18:00 Welcome and Dinner
24 - 31 October - project work
- 8:00-9:00 breakfast
- generally working a lot
- also boardgames, walks, sports
- talks and seminars TBD
Friday, 1 November - demo day and closing thoughts
- retro meeting (mad, sad, glad format)
- project presentations
- saying goodbye
Venue
Nagymaros, Hungary
Mihály utca
Our home for the week is a nice house in Nagymaros, close to the train station with lovely views over the river and surrounding hills. The house has communal areas, a kitchen, and rooms with 2-4 beds in each.
Speakers and Mentors
full list of speakers TBD
Ferenc Huszár
Professor of Machine Learning, Cambridge
I studied Computer Engineering at BME (Budapest) and got into machine learning after joining computational neuroscience research group. I did a PhD in Probabilistic Machine Learning at Cambridge. I worked in tech for 10 years, including startups, venture capital, and four years at Twitter. I joined Cambridge as an Associate Professor in 2020, where my group does research on the theory of deep learning. I've been running AI retreats since 2022.
More speakers TBD
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Participants
Full list of participants TBA
Participants TBA
Short Bio