Berner, Julius

28 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

TMLR 2025 Enabling Automatic Differentiation with Mollified Graph Neural Operators Ryan Y. Lin, Julius Berner, Valentin Duruisseaux, David Pitt, Daniel Leibovici, Jean Kossaifi, Kamyar Azizzadenesheli, Anima Anandkumar

NeurIPS 2025 Guided Diffusion Sampling on Function Spaces with Applications to PDEs Jiachen Yao, Abbas Mammadov, Julius Berner, Gavin Kerrigan, Jong Chul Ye, Kamyar Azizzadenesheli, Anima Anandkumar

CVPR 2025 Improving Diffusion Inverse Problem Solving with Decoupled Noise Annealing Bingliang Zhang, Wenda Chu, Julius Berner, Chenlin Meng, Anima Anandkumar, Yang Song

ICLR 2025 Robust Representation Consistency Model via Contrastive Denoising Jiachen Lei, Julius Berner, Jiongxiao Wang, Zhongzhu Chen, Chaowei Xiao, Zhongjie Ba, Kui Ren, Jun Zhu, Anima Anandkumar

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

NeurIPSW 2024 Beyond Closure Models: Learning Chaotic-Systems via Physics-Informed Neural Operators Chuwei Wang, Julius Berner, Zongyi Li, Di Zhou, Jiayun Wang, Jane Bae, Anima Anandkumar

ICML 2024 DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training Zhongkai Hao, Chang Su, Songming Liu, Julius Berner, Chengyang Ying, Hang Su, Anima Anandkumar, Jian Song, Jun Zhu

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

ICML 2024 Neural Operators with Localized Integral and Differential Kernels Miguel Liu-Schiaffini, Julius Berner, Boris Bonev, Thorsten Kurth, Kamyar Azizzadenesheli, Anima Anandkumar

ICLRW 2024 Neural Operators with Localized Integral and Differential Kernels Miguel Liu-Schiaffini, Julius Berner, Boris Bonev, Thorsten Kurth, Kamyar Azizzadenesheli, Anima Anandkumar

ICLRW 2024 Physics-Informed Neural Networks for Sampling Jingtong Sun, Julius Berner, Kamyar Azizzadenesheli, Anima Anandkumar

NeurIPS 2024 Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs Md Ashiqur Rahman, Robert Joseph George, Mogab Elleithy, Daniel Leibovici, Zongyi Li, Boris Bonev, Colin White, Julius Berner, Raymond A. Yeh, Jean Kossaifi, Kamyar Azizzadenesheli, Anima Anandkumar

ICML 2024 Solving Poisson Equations Using Neural Walk-on-Spheres Hong Chul Nam, Julius Berner, Anima Anandkumar

ICLRW 2024 Solving Poisson Equations Using Neural Walk-on-Spheres Hong Chul Nam, Julius Berner, Anima Anandkumar

ICMLW 2024 Towards Enforcing Hard Physics Constraints in Operator Learning Frameworks Valentin Duruisseaux, Miguel Liu-Schiaffini, Julius Berner, Anima Anandkumar

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

ICLR 2023 Learning ReLU Networks to High Uniform Accuracy Is Intractable Julius Berner, Philipp Grohs, Felix Voigtlaender

NeurIPS 2023 Mathematical Capabilities of ChatGPT Simon Frieder, Luca Pinchetti, Chevalier, Ryan-Rhys Griffiths, Tommaso Salvatori, Thomas Lukasiewicz, Philipp Petersen, Julius Berner

NeurIPSW 2023 Physics-Informed Neural Operators with Exact Differentiation on Arbitrary Geometries Colin White, Julius Berner, Jean Kossaifi, Mogab Elleithy, David Pitt, Daniel Leibovici, Zongyi Li, Kamyar Azizzadenesheli, Anima Anandkumar

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

NeurIPS 2020 Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning Julius Berner, Markus Dablander, Philipp Grohs

NeurIPS 2019 How Degenerate Is the Parametrization of Neural Networks with the ReLU Activation Function? Dennis Maximilian Elbrächter, Julius Berner, Philipp Grohs