Lorenz Richter
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Solving high-dimensional Hamilton–Jacobi–Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space
N Nüsken, L Richter
Partial differential equations and applications 2, 1-48, 2021
Solving high-dimensional parabolic PDEs using the tensor train format
L Richter, L Sallandt, N Nüsken
International Conference on Machine Learning, 8998-9009, 2021
Variational characterization of free energy: theory and algorithms
C Hartmann, L Richter, C Schütte, W Zhang
Entropy 19 (11), 626, 2017
Variational approach to rare event simulation using least-squares regression
C Hartmann, O Kebiri, L Neureither, L Richter
Chaos: An Interdisciplinary Journal of Nonlinear Science 29 (6), 2019
VarGrad: a low-variance gradient estimator for variational inference
L Richter, A Boustati, N Nüsken, F Ruiz, OD Akyildiz
Advances in Neural Information Processing Systems 33, 13481-13492, 2020
An optimal control perspective on diffusion-based generative modeling
J Berner, L Richter, K Ullrich
arXiv preprint arXiv:2211.01364, 2022
Interpolating between BSDEs and PINNs: deep learning for elliptic and parabolic boundary value problems
N Nüsken, L Richter
arXiv preprint arXiv:2112.03749, 2021
Early Crop Classification via Multi-Modal Satellite Data Fusion and Temporal Attention
F Weilandt, R Behling, R Goncalves, A Madadi, L Richter, T Sanona, ...
Remote Sensing 15 (3), 799, 2023
Robust SDE-based variational formulations for solving linear PDEs via deep learning
L Richter, J Berner
International Conference on Machine Learning, 18649-18666, 2022
Nonasymptotic bounds for suboptimal importance sampling
C Hartmann, L Richter
arXiv preprint arXiv:2102.09606, 2021
Improved sampling via learned diffusions
L Richter, J Berner, GH Liu
arXiv preprint arXiv:2307.01198, 2023
Solving high-dimensional PDEs, approximation of path space measures and importance sampling of diffusions
L Richter
BTU Cottbus-Senftenberg, 2021
Error bounds for model reduction of feedback-controlled linear stochastic dynamics on Hilbert spaces
S Becker, C Hartmann, M Redmann, L Richter
Stochastic Processes and their Applications 149, 107-141, 2022
Improving control based importance sampling strategies for metastable diffusions via adapted metadynamics
ER Borrell, J Quer, L Richter, C Schütte
arXiv preprint arXiv:2206.06628, 2022
Model order reduction for (stochastic-) delay equations with error bounds
S Becker, L Richter
arXiv preprint arXiv:2008.12288, 2020
Transgressing the Boundaries: Towards a Rigorous Understanding of Deep Learning and Its (Non-)Robustness
C Hartmann, L Richter
AI-Limits and Prospects of Artificial Intelligence 4, 43, 2023
Fast and unified path gradient estimators for normalizing flows
L Vaitl, L Winkler, L Richter, P Kessel
The Twelfth International Conference on Learning Representations, 2023
From continuous-time formulations to discretization schemes: tensor trains and robust regression for BSDEs and parabolic PDEs
L Richter, L Sallandt, N Nüsken
arXiv preprint arXiv:2307.15496, 2023
Deep learning based visual inspection of facets and p-sides for efficient quality control of diode lasers
C Zink, M Ekterai, D Martin, W Clemens, A Maennel, K Mundinger, ...
High-Power Diode Laser Technology XXI 12403, 94-112, 2023
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