From the 1 of 12 linked papers with an AI index.
12 papers
Lecture Notes: Convex Optimization
Andreas Habring
These lecture notes introduce the theory and algorithms of convex optimization, covering existence results, projected subgradient descent, proximal‑gradient and accelerated gradien…
Ergodicity of Langevin Dynamics and its Discretizations for Non-smooth Potentials
Lorenz Fruehwirth, Andreas Habring
This article is concerned with sampling from Gibbs distributions using Markov chain Monte Carlo methods. In particular, we investigate Langevin dynamics in…
Generating Physically Consistent Molecules with Energy-Based Models
Christoph Griesbacher, Lea Bogensperger, Andreas Habring +1
Molecules in equilibrium follow a Boltzmann distribution, making the underlying energy landscape a physically grounded modeling objective. However, such landscapes are difficult to…
Forward-KL Convergence of Time-Inhomogeneous Langevin Diffusions
Andreas Habring, Martin Zach
Many practical samplers rely on time-dependent drifts -- often induced by annealing or tempering schedules -- to improve exploration and stability. This motivates a unified non-asy…
Time-Inhomogeneous Preconditioned Langevin Dynamics
Alexander Falk, Laurenz Nagler, Andreas Habring +1
Langevin sampling from distributions of the form faces two major challenges: (global) mode coverage and (local) mode exploration. The first challenge is…
The Gaussian Latent Machine: Efficient Prior and Posterior Sampling for Inverse Problems
Muhamed Kuric, Martin Zach, Andreas Habring +2
We consider the problem of sampling from a product-of-experts-type model that encompasses many standard prior and posterior distributions commonly found in Bayesian imaging. We sho…