Number of items: **11**.

## 2024

Polzin, Robert and Klebanov, Ilja and Nüsken, Nikolas and Koltai, Péter
(2024)
*Coherent set identification via direct low rank maximum likelihood estimation.*
Journal of Nonlinear Science
.

## 2023

Coghi, Michele and Nilssen, Torstein and Nüsken, Nikolas and Reich, Sebastian
(2023)
*Rough McKean–Vlasov dynamics for robust ensemble Kalman filtering.*
The Annals of Applied Probability, 33
(6b).
pp. 5693-5752.

Polzin, Robert and Klebanov, Ilja and Nüsken, Nikolas and Koltai, Péter
(2023)
*Nonnegative matrix factorization for coherent set identification by direct low rank maximum likelihood estimation.*
arXiv
.
pp. 1-43.
(Unpublished)

Richter, Lorenz and Sallandt, Leon and Nüsken, Nikolas
(2023)
*From continuous-time formulations to discretization schemes: tensor trains and robust regression for BSDEs and parabolic PDEs.*
Preprint
.
(Unpublished)

Nüsken, Nikolas and Richter, Lorenz
(2023)
*Interpolating Between BSDEs and PINNs: Deep Learning for Elliptic and Parabolic Boundary Value Problems.*
Journal of Machine Learning, 2
.
pp. 31-64.

## 2021

Coghi, Michele and Nilssen, Torstein and Nüsken, Nikolas
(2021)
*Rough McKean-Vlasov dynamics for robust ensemble Kalman filtering.*
arXive
.
pp. 1-41.
(Submitted)

Nüsken, Nikolas and Richter, Lorenz
(2021)
*Solving high-dimensional Hamilton–Jacobi–Bellman PDEs
using neural networks: perspectives from the theory of
controlled diffusions and measures on path space.*
Partial Differential Equations and Applications, 2
(48).
pp. 1-48.

Nüsken, Nikolas and Renger, D.R. Michiel
(2021)
*Stein Variational Gradient Descent:many-particle and long-time asymptotics.*
arxiv preprint
.
pp. 1-25.
(Submitted)

Richter, Lorenz and Sallandt, Leon and Nüsken, Nikolas
(2021)
*Solving high-dimensional parabolic PDEs using the tensor train format.*
Proceedings of the 38th International Conferenceon Machine Learning, 139
.
pp. 8998-9009.

## 2020

Richter, Lorenz and Boustati, Ayman and Nüsken, Nikolas and Ruiz, Francisco J. R. and Akyildiz, Ömer Deniz
(2020)
*VarGrad: A Low-Variance Gradient Estimator for Variational Inference.*
Advances in Neural Information Processing Systems 2020
.
pp. 1-25.
(Submitted)

Garbuno-Inigo, Alfredo and Nüsken, Nikolas and Reich, Sebastian
(2020)
*Affine Invariant Interacting Langevin Dynamics for Bayesian Inference.*
SIAM J. APPLIED DYNAMICAL SYSTEMS, 19
(3).
pp. 1633-1658.

This list was generated on **Wed Nov 13 18:34:01 2024 CET**.