Semantics of Integrating and Differentiating Singularities

Parameter Expanded Stochastic Gradient Descent Markov Chain Monte Carlo

Over-parameterised Shallow Neural Networks with Asymmetrical Node Scaling: Global Convergence Guarantees and Feature Learning

Mitigating Covariate Shift in Behavioral Cloning via Robust Stationary Distribution Correction.

Analysing Feature Learning of Gradient Descent Using Periodic Functions

Transformers Can Perform Distributionally-robust Optimisation through In-context Learning

Variational Partial Group Convolutions for Input-Aware Partial Equivariance of Rotations and Color-Shifts.

An Infinite-Width Analysis on the Jacobian-Regularised Training of a Neural Network.

Probabilistic programming interfaces for random graphs: Markov categories, graphons, and nominal sets.

Alpha-stable Convergence of Heavy-tailed Infinitely-wide Neural Networks