Video Lectures

In a joint work with Laurent Côté we show the following result. Any Lagrangian plane in the cotangent bundle of an open Riemann surface which coincides with a cotangent fibre outside of some compact subset, is compactly supported Hamiltonian...

I discuss string theory on AdS3xS3xT4 in the tensionless limit, with one unit of NS-NS flux. This theory is conjectured to be dual to the symmetric product orbifold CFT. I show how to compute the full string partition function on various locally...

Many challenging problems in modern applications amount to finding relevant results from an enormous output space of potential candidates, for example, finding the best matching product from a large catalog or suggesting related search phrases on a...

Classical algorithms typically provide "one size fits all" performance, and do not leverage properties or patterns in their inputs. A recent line of work aims to address this issue by developing algorithms that use machine learning predictions to...

Over the last decade it has become clear that there is a close connection between the BPS sector of N=2 supersymmetric field theories in four dimensions and the exact WKB method for analysis of ordinary differential equations (Schrodinger equations...

Suppose you are monitoring discrete events in real time. Can you predict what events will happen in the future, and when? Can you fill in past events that you may have missed? A probability model that supports such reasoning is the neural Hawkes...

A brief review will be provided first on how deep learning has disrupted speech recognition and language processing industries since 2009. Then connections will be drawn between the techniques (deep learning or otherwise) for modeling speech and...

I will present enhanced corrections to the entanglement entropy of a subsystem in holographic states. These corrections appear near phase transitions in the entanglement entropy due to competing extremal surfaces, and they are holographic avatars...

There are three core orthogonal problems in reinforcement learning: (1) Crediting actions (2) generalizing across rich observations (3) Exploring to discover the information necessary for learning. Good solutions to pairs of these problems are...

Probably Approximately Correct (PAC) learning has attempted to analyse the generalisation of learning systems within the statistical learning framework. It has been referred to as a ‘worst case’ analysis, but the tools have been extended to analyse...