74 citations · 120 across the 41 of their papers we have counts for
4 papers · 1 filter
Instance-Dependent Generalization Bounds via Optimal Transport
Songyan Hou, Parnian Kassraie, Anastasis Kratsios +2
Existing generalization bounds fail to explain crucial factors that drive the generalization of modern neural networks. Since such bounds often hold uniformly over all parameters,…
Designing Universal Causal Deep Learning Models: The Case of Infinite-Dimensional Dynamical Systems from Stochastic Analysis
Luca Galimberti, Anastasis Kratsios, Giulia Livieri
Several non-linear operators in stochastic analysis, such as solution maps to stochastic differential equations, depend on a temporal structure which is not leveraged by contempora…
Do ReLU Networks Have An Edge When Approximating Compactly-Supported Functions?
Anastasis Kratsios, Behnoosh Zamanlooy
We study the problem of approximating compactly-supported integrable functions while implementing their support set using feedforward neural networks. Our first main result transcr…
Designing Universal Causal Deep Learning Models: The Geometric (Hyper)Transformer
Beatrice Acciaio, Anastasis Kratsios, Gudmund Pammer
Several problems in stochastic analysis are defined through their geometry, and preserving that geometric structure is essential to generating meaningful predictions. Nevertheless,…