activity
20232026
most citedGeneralization Bounds: Perspectives from Information Theory and PAC-Bayes

6 citations · 6 across the 4 of their papers we have counts for

collaborators

5 papers

eess.SY2026

Transition Path Sampling Using Koopman Operators and Exit-Time Optimal Control

Boya Hou, Shane Wang, Siddharth Ambekar +2

Sampling transitions between metastable states is a central problem in dynamical systems theory and molecular dynamics in particular. A key challenge is the existence of high free-…

math.DS2026

Spatially-Coupled Network RNA Velocities: A Control-Theoretic Perspective

Boya Hou, Maxim Raginsky, Abhishek Pandey +1

RNA velocity is an important model that combines cellular spliced and unspliced RNA counts to infer dynamical properties of various regulatory functions. Despite its wide applicabi…

math.OC2024

Revisiting Stochastic Realization Theory using Functional Itô Calculus

Tanya Veeravalli, Maxim Raginsky

This paper considers the problem of constructing finite-dimensional state space realizations for stochastic processes that can be represented as the outputs of a certain type of a…

cs.CL2024

Transformer-Based Models Are Not Yet Perfect At Learning to Emulate Structural Recursion

Dylan Zhang, Curt Tigges, Zory Zhang +3

This paper investigates the ability of transformer-based models to learn structural recursion from examples. Recursion is a universal concept in both natural and formal languages.…

cs.LG2023★ 6 cited

Generalization Bounds: Perspectives from Information Theory and PAC-Bayes

Fredrik Hellström, Giuseppe Durisi, Benjamin Guedj +1

A fundamental question in theoretical machine learning is generalization. Over the past decades, the PAC-Bayesian approach has been established as a flexible framework to address t…