Lorenz Richter

39 papers A* 9Journal 30
YearRankTypeTitle / Venue / Authors
2026 J jnl
Bridge Matching Sampler: Scalable Sampling via Generalized Fixed-Point Diffusion Matching.
CoRR
Denis Blessing, Lorenz Richter, Julius Berner, Egor Malitskiy, Gerhard Neumann
2026 J jnl
From discrete-time policies to continuous-time diffusion samplers: Asymptotic equivalences and faster training.
Trans. Mach. Learn. Res.
Julius Berner, Lorenz Richter, Marcin Sendera, Jarrid Rector-Brooks, Nikolay Malkin
2025 J jnl
From discrete-time policies to continuous-time diffusion samplers: Asymptotic equivalences and faster training.
CoRR
Julius Berner, Lorenz Richter, Marcin Sendera, Jarrid Rector-Brooks, Nikolay Malkin
2025 J jnl
Meta-learning For Few-Shot Time Series Crop Type Classification: A Benchmark On The EuroCropsML Dataset.
CoRR
Joana Reuss, Jan MacDonald, Simon Becker, Konrad Schultka, Lorenz Richter, Marco Körner
2025 A* conf
Reinforcement Learning with Random Time Horizons.
ICML
Enric Ribera Borrell, Lorenz Richter, Christof Schütte
2025 J jnl
Reinforcement Learning with Random Time Horizons.
CoRR
Enric Ribera Borrell, Lorenz Richter, Christof Schütte
2025 A* conf
Sequential Controlled Langevin Diffusions.
ICLR
Junhua Chen, Lorenz Richter, Julius Berner, Denis Blessing, Gerhard Neumann, Anima Anandkumar
2025 J jnl
Trust Region Constrained Measure Transport in Path Space for Stochastic Optimal Control and Inference.
CoRR
Denis Blessing, Julius Berner, Lorenz Richter, Carles Domingo-Enrich, Yuanqi Du, Arash Vahdat, Gerhard Neumann
2025 A* conf
Underdamped Diffusion Bridges with Applications to Sampling.
ICLR
Denis Blessing, Julius Berner, Lorenz Richter, Gerhard Neumann
2025 J jnl
Underdamped Diffusion Bridges with Applications to Sampling.
CoRR
Denis Blessing, Julius Berner, Lorenz Richter, Gerhard Neumann
2024 J jnl
An optimal control perspective on diffusion-based generative modeling.
Trans. Mach. Learn. Res.
Julius Berner, Lorenz Richter, Karen Ullrich
2024 A* conf
Bridging discrete and continuous state spaces: Exploring the Ehrenfest process in time-continuous diffusion models.
ICML
Ludwig Winkler, Lorenz Richter, Manfred Opper
2024 J jnl
Bridging discrete and continuous state spaces: Exploring the Ehrenfest process in time-continuous diffusion models.
CoRR
Ludwig Winkler, Lorenz Richter, Manfred Opper
2024 J jnl
Dynamical Measure Transport and Neural PDE Solvers for Sampling.
CoRR
Jingtong Sun, Julius Berner, Lorenz Richter, Marius Zeinhofer, Johannes Müller, Kamyar Azizzadenesheli, Anima Anandkumar
2024 J jnl
EuroCropsML: A Time Series Benchmark Dataset For Few-Shot Crop Type Classification.
CoRR
Joana Reuss, Jan MacDonald, Simon Becker, Lorenz Richter, Marco Körner
2024 J jnl
Fast and Unified Path Gradient Estimators for Normalizing Flows.
CoRR
Lorenz Vaitl, Ludwig Winkler, Lorenz Richter, Pan Kessel
2024 A* conf
Fast and unified path gradient estimators for normalizing flows.
ICLR
Lorenz Vaitl, Ludwig Winkler, Lorenz Richter, Pan Kessel
2024 J jnl
From continuous-time formulations to discretization schemes: tensor trains and robust regression for BSDEs and parabolic PDEs.
J. Mach. Learn. Res.
Lorenz Richter, Leon Sallandt, Nikolas Nüsken
2024 A* conf
Improved sampling via learned diffusions.
ICLR
Lorenz Richter, Julius Berner
2024 J jnl
Improving Control Based Importance Sampling Strategies for Metastable Diffusions via Adapted Metadynamics.
SIAM J. Sci. Comput.
Enric Ribera Borrell, Jannes Quer, Lorenz Richter, Christof Schütte
2024 J jnl
Nonasymptotic Bounds for Suboptimal Importance Sampling.
SIAM/ASA J. Uncertain. Quantification
Carsten Hartmann, Lorenz Richter
2024 J jnl
Sequential Controlled Langevin Diffusions.
CoRR
Junhua Chen, Lorenz Richter, Julius Berner, Denis Blessing, Gerhard Neumann, Anima Anandkumar
2023 J jnl
Early Crop Classification via Multi-Modal Satellite Data Fusion and Temporal Attention.
Remote. Sens.
Frank Weilandt, Robert Behling, Romulo Goncalves, Arash Madadi, Lorenz Richter, Tiago Sanona, Daniel Spengler, Jona Welsch
2023 J jnl
From continuous-time formulations to discretization schemes: tensor trains and robust regression for BSDEs and parabolic PDEs.
CoRR
Lorenz Richter, Leon Sallandt, Nikolas Nüsken
2023 J jnl
Improved sampling via learned diffusions.
CoRR
Lorenz Richter, Julius Berner
2023 J jnl
Transgressing the boundaries: towards a rigorous understanding of deep learning and its (non-)robustness.
CoRR
Carsten Hartmann, Lorenz Richter
2022 J jnl
An optimal control perspective on diffusion-based generative modeling.
CoRR
Julius Berner, Lorenz Richter, Karen Ullrich
2022 A* conf
Robust SDE-Based Variational Formulations for Solving Linear PDEs via Deep Learning.
ICML
Lorenz Richter, Julius Berner
2022 J jnl
Robust SDE-Based Variational Formulations for Solving Linear PDEs via Deep Learning.
CoRR
Lorenz Richter, Julius Berner
2021 J jnl
Interpolating between BSDEs and PINNs - deep learning for elliptic and parabolic boundary value problems.
CoRR
Nikolas Nüsken, Lorenz Richter
2021 J jnl
Nonasymptotic bounds for suboptimal importance sampling.
CoRR
Carsten Hartmann, Lorenz Richter
2021 A* conf
Solving high-dimensional parabolic PDEs using the tensor train format.
ICML
Lorenz Richter, Leon Sallandt, Nikolas Nüsken
2021 J jnl
Solving high-dimensional parabolic PDEs using the tensor train format.
CoRR
Lorenz Richter, Leon Sallandt, Nikolas Nüsken
2020 J jnl
Model Order Reduction for (Stochastic-) Delay Equations With Error Bounds.
CoRR
Simon Becker, Lorenz Richter
2020 J jnl
Solving high-dimensional Hamilton-Jacobi-Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space.
CoRR
Nikolas Nüsken, Lorenz Richter
2020 A* conf
VarGrad: A Low-Variance Gradient Estimator for Variational Inference.
NeurIPS
Lorenz Richter, Ayman Boustati, Nikolas Nüsken, Francisco J. R. Ruiz, Ömer Deniz Akyildiz
2020 J jnl
VarGrad: A Low-Variance Gradient Estimator for Variational Inference.
CoRR
Lorenz Richter, Ayman Boustati, Nikolas Nüsken, Francisco J. R. Ruiz, Ömer Deniz Akyildiz
2019 J jnl
Feedback control theory & Model order reduction for stochastic equations.
CoRR
Simon Becker, Carsten Hartmann, Martin Redmann, Lorenz Richter
2017 J jnl
Variational Characterization of Free Energy: Theory and Algorithms.
Entropy
Carsten Hartmann, Lorenz Richter, Christof Schütte, Wei Zhang