Richter, Lorenz

16 publications

TMLR 2026 From Discrete-Time Policies to Continuous-Time Diffusion Samplers: Asymptotic Equivalences and Faster Training Julius Berner, Lorenz Richter, Marcin Sendera, Jarrid Rector-Brooks, Nikolay Malkin

ICML 2025 Reinforcement Learning with Random Time Horizons Enric Ribera Borrell, Lorenz Richter, Christof Schuette

ICLR 2025 Sequential Controlled Langevin Diffusions Junhua Chen, Lorenz Richter, Julius Berner, Denis Blessing, Gerhard Neumann, Anima Anandkumar

NeurIPS 2025 Trust Region Constrained Measure Transport in Path Space for Stochastic Optimal Control and Inference Denis Blessing, Julius Berner, Lorenz Richter, Carles Domingo-Enrich, Yuanqi Du, Arash Vahdat, Gerhard Neumann

ICLR 2025 Underdamped Diffusion Bridges with Applications to Sampling Denis Blessing, Julius Berner, Lorenz Richter, Gerhard Neumann

ICLRW 2025 Underdamped Diffusion Bridges with Applications to Sampling Denis Blessing, Julius Berner, Lorenz Richter, Gerhard Neumann

TMLR 2024 An Optimal Control Perspective on Diffusion-Based Generative Modeling Julius Berner, Lorenz Richter, Karen Ullrich

ICML 2024 Bridging Discrete and Continuous State Spaces: Exploring the Ehrenfest Process in Time-Continuous Diffusion Models Ludwig Winkler, Lorenz Richter, Manfred Opper

ICLR 2024 Fast and Unified Path Gradient Estimators for Normalizing Flows Lorenz Vaitl, Ludwig Winkler, Lorenz Richter, Pan Kessel

JMLR 2024 From Continuous-Time Formulations to Discretization Schemes: Tensor Trains and Robust Regression for BSDEs and Parabolic PDEs Lorenz Richter, Leon Sallandt, Nikolas Nüsken

ICLR 2024 Improved Sampling via Learned Diffusions Lorenz Richter, Julius Berner

ICMLW 2023 Improved Sampling via Learned Diffusions Lorenz Richter, Julius Berner, Guan-Horng Liu

NeurIPSW 2022 An Optimal Control Perspective on Diffusion-Based Generative Modeling Julius Berner, Lorenz Richter, Karen Ullrich

ICML 2022 Robust SDE-Based Variational Formulations for Solving Linear PDEs via Deep Learning Lorenz Richter, Julius Berner

ICML 2021 Solving High-Dimensional Parabolic PDEs Using the Tensor Train Format Lorenz Richter, Leon Sallandt, Nikolas Nüsken

NeurIPS 2020 VarGrad: A Low-Variance Gradient Estimator for Variational Inference Lorenz Richter, Ayman Boustati, Nikolas Nüsken, Francisco Ruiz, Omer Deniz Akyildiz