Moeller, Michael

24 publications

NeurIPS 2025 Neural Atlas Graphs for Dynamic Scene Decomposition and Editing Jan Philipp Schneider, Pratik Singh Bisht, Ilya Chugunov, Andreas Kolb, Michael Moeller, Felix Heide

CVPR 2025 QuCOOP: A Versatile Framework for Solving Composite and Binary-Parametrised Problems on Quantum Annealers Natacha Kuete Meli, Vladislav Golyanik, Marcel Seelbach Benkner, Michael Moeller

CVPRW 2025 Training Data Reconstruction: Privacy Due to Uncertainty? Christina Runkel, Kanchana Vaishnavi Gandikota, Jonas Geiping, Carola-Bibiane Schönlieb, Michael Moeller

ICMLW 2024 3D Shape Completion with Test-Time Training Michael Schopf-Kuester, Zorah Lähner, Michael Moeller

ICML 2024 Implicit Representations for Constrained Image Segmentation Jan Philipp Schneider, Mishal Fatima, Jovita Lukasik, Andreas Kolb, Margret Keuper, Michael Moeller

CVPR 2023 CCuantuMM: Cycle-Consistent Quantum-Hybrid Matching of Multiple Shapes Harshil Bhatia, Edith Tretschk, Zorah Lähner, Marcel Seelbach Benkner, Michael Moeller, Christian Theobalt, Vladislav Golyanik

NeurIPSW 2023 Implicit Representations for Image Segmentation Jan Philipp Schneider, Mishal Fatima, Jovita Lukasik, Andreas Kolb, Margret Keuper, Michael Moeller

NeurIPS 2023 Kissing to Find a Match: Efficient Low-Rank Permutation Representation Hannah Dröge, Zorah Lähner, Yuval Bahat, Onofre Martorell Nadal, Felix Heide, Michael Moeller

NeurIPSW 2023 On the Direct Alignment of Latent Spaces Zorah Lähner, Michael Moeller

ICLR 2023 QuAnt: Quantum Annealing with Learnt Couplings Marcel Seelbach Benkner, Maximilian Krahn, Edith Tretschk, Zorah Lähner, Michael Moeller, Vladislav Golyanik

ICCV 2023 SIGMA: Scale-Invariant Global Sparse Shape Matching Maolin Gao, Paul Roetzer, Marvin Eisenberger, Zorah Lähner, Michael Moeller, Daniel Cremers, Florian Bernard

ECCV 2022 Intrinsic Neural Fields: Learning Functions on Manifolds Lukas Koestler, Daniel Grittner, Michael Moeller, Daniel Cremers, Zorah Lähner

ICLR 2022 Stochastic Training Is Not Necessary for Generalization Jonas Geiping, Micah Goldblum, Phil Pope, Michael Moeller, Tom Goldstein

NeurIPSW 2021 DARTS for Inverse Problems: A Study on Stability Jonas Geiping, Jovita Lukasik, Margret Keuper, Michael Moeller

ICCV 2021 Q-Match: Iterative Shape Matching via Quantum Annealing Marcel Seelbach Benkner, Zorah Lähner, Vladislav Golyanik, Christof Wunderlich, Christian Theobalt, Michael Moeller

ICLR 2021 Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching Jonas Geiping, Liam H Fowl, W. Ronny Huang, Wojciech Czaja, Gavin Taylor, Michael Moeller, Tom Goldstein

NeurIPS 2020 Inverting Gradients - How Easy Is It to Break Privacy in Federated Learning? Jonas Geiping, Hartmut Bauermeister, Hannah Dröge, Michael Moeller

NeurIPSW 2020 Learning Spectral Regularizations for Linear Inverse Problems Hartmut Bauermeister, Martin Burger, Michael Moeller

ICLR 2020 Truth or Backpropaganda? an Empirical Investigation of Deep Learning Theory Micah Goldblum, Jonas Geiping, Avi Schwarzschild, Michael Moeller, Tom Goldstein

NeurIPSW 2019 Energy Dissipation with Plug-and-Play Priors Hendrik Sommerhoff, Andreas Kolb, Michael Moeller

ECCV 2018 Lifting Layers: Analysis and Applications Peter Ochs, Tim Meinhardt, Laura Leal-Taixe, Michael Moeller

ICLR 2018 Proximal Backpropagation Thomas Frerix, Thomas Möllenhoff, Michael Moeller, Daniel Cremers

CVPR 2016 Sublabel-Accurate Relaxation of Nonconvex Energies Thomas Mollenhoff, Emanuel Laude, Michael Moeller, Jan Lellmann, Daniel Cremers

ICCV 2015 Learning Nonlinear Spectral Filters for Color Image Reconstruction Michael Moeller, Julia Diebold, Guy Gilboa, Daniel Cremers