57 citations · 94 across the 16 of their papers we have counts for
18 papers
Information-Theoretic Foundations of Online Temperature Sampling
Jin Sima, Nikolaos Papagiannis, Ananth Grama +1
Repetitive, degenerate generation is a persistent failure of LLM decoding, and the standard remedies (temperature, nucleus, and top- sampling) are static heuristics. By Kac's le…
Ensemble Kalman inversion with non-smooth regularization
Simon Weissmann
This paper investigates ensemble Kalman inversion (EKI) for variational inverse problems with convex, potentially non-smooth regularization. While deterministic EKI and its Tikhono…
A Stochastic Gradient Descent Approach to Design Policy Gradient Methods for LQR
Bowen Song, Simon Weissmann, Mathias Staudigl +1
In this work, we propose a stochastic gradient descent (SGD) framework to design data-driven policy gradient descent algorithms for the linear quadratic regulator problem. Two alte…
Affine invariant interacting Langevin dynamics in Markov chain importance sampling for rare event estimation
Jason Beh, Jérôme Morio, Florian Simatos +1
This work considers the framework of Markov chain importance sampling~(MCIS), in which one employs a Markov chain Monte Carlo~(MCMC) scheme to sample particles approaching the opti…
Derivative-free stochastic bilevel optimization for inverse problems
Mathias Staudigl, Simon Weissmann, Tristan van Leeuwen
Inverse problems are key issues in several scientific areas, including signal processing and medical imaging. Data-driven approaches for inverse problems aim for learning model and…
The Ensemble Kalman Filter for Dynamic Inverse Problems
Simon Weissmann, Neil K. Chada, Xin T. Tong
In inverse problems, the goal is to estimate unknown model parameters from noisy observational data. Traditionally, inverse problems are solved under the assumption of a fixed forw…