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Hertrich, Johannes

  1. Generative Sliced MMD Flows with Riesz Kernels
    2023/05/19 by Johannes Hertrich, Hertrich, Johannes, Christian Wald +5 · 7 citations
    Economics, Econometrics and Finance · Engineering · #FOS: Computer and information sciences #FOS: Mathematics #Lattice Boltzmann Simulation Studies #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Probability (math.PR) #Stochastic processes and financial applications
  2. DeepInverse: A Python package for solving imaging inverse problems with deep learning
    2025/05/26 by Julián Tachella, Matthieu Terris, Tachella, Julián +50 · 16 citations
    Mathematics · Computer Science · Engineering · #Statistical and numerical algorithms #Computational Physics and Python Applications #Sparse and Compressive Sensing Techniques
  3. Posterior Sampling Based on Gradient Flows of the MMD with Negative Distance Kernel
    2023/10/04 by Hagemann, Paul, Hertrich, Johannes, Altekrüger, Fabian +3 · 3 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Probability (math.PR)
  4. Fast Summation of Radial Kernels via QMC Slicing
    2024/10/02 by Hertrich, Johannes, Jahn, Tim, Quellmalz, Michael · 3 citations
    #Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Numerical Analysis (math.NA)
  5. On the Relation between Rectified Flows and Optimal Transport
    2025/05/26 by Johannes Hertrich, Antonin Chambolle, Hertrich, Johannes +3 · 1 voice · 4 citations
    Engineering · #Traffic control and management #cs.LG #math.PR #stat.ML
  6. Wasserstein Gradient Flows of MMD Functionals with Distance Kernel and Cauchy Problems on Quantile Functions
    2024/08/14 by Richard Duong, Viktor Stein, Duong, Richard +7 · 2 citations
    Economics, Econometrics and Finance · Mathematics · #35B99 (Secondary) #46N10 #49Q22 (Primary) #Analysis of PDEs (math.AP) #FOS: Computer and information sciences #FOS: Mathematics #Geometric Analysis and Curvature Flows #Machine Learning (stat.ML) #Nonlinear Partial Differential Equations #Stochastic processes and financial applications
  7. Learning from small data sets: Patch-based regularizers in inverse problems for image reconstruction
    2023/12/27 by Moritz Piening, Fabian Altekrüger, Piening, Moritz +9 · 2 citations
    Computer Science · Mathematics · Medicine · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Image and Video Processing (eess.IV) #Machine Learning (cs.LG) #Medical Imaging Techniques and Applications #Probability (math.PR) #Statistical Methods and Inference #electronic engineering #information engineering
  8. Plug-and-Play Half-Quadratic Splitting for Ptychography
    2024/12/03 by Alexander Denker, Johannes Hertrich, Denker, Alexander +9 · 2 citations
    Physics and Astronomy · Earth and Planetary Sciences · #Advanced X-ray Imaging Techniques #Geophysics and Gravity Measurements #Astrophysical Phenomena and Observations
  9. Importance Corrected Neural JKO Sampling
    2024/07/29 by Johannes Hertrich, Robert Gruhlke, Hertrich, Johannes +1 · 1 citation
    Computer Science · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Probability (math.PR)
  10. Learning Regularization Functionals for Inverse Problems: A Comparative Study
    2025/10/02 by Hertrich, Johannes, Wong, Hok Shing, Denker, Alexander +16 · 3 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Numerical Analysis (math.NA) #Optimization and Control (math.OC)
  11. Iterative Importance Fine-tuning of Diffusion Models
    2025/02/06 by Alexander Denker, Denker, Alexander, Shreyas Padhy +5 · 1 citation
    Computer Science · #68T07 #Advanced Mathematical Modeling in Engineering #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #I.2.6 #I.4.9 #Image and Video Processing (eess.IV) #Machine Learning (cs.LG) #Probability (math.PR) #electronic engineering #information engineering