Michael Moeller

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 41

Top Topics

Inverse Problems

Low Quality Images

Top Venues

Publications

Alexander Auras, Kanchana Vaishnavi Gandikota, Hannah Dröge, Michael Moeller
Robustness and Exploration of Variational and Machine Learning Approaches to Inverse Problems: An Overview. CoRR (2024)
Kanchana Vaishnavi Gandikota, Paramanand Chandramouli, Hannah Dröge, Michael Moeller
Evaluating Adversarial Robustness of Low dose CT Recovery. CoRR (2024)
Bhaskar Choubey, Hendrik Sommerhoff, Michael Moeller, Andreas Kolb
Variable layout CMOS pixels for end-to-end learning in task specific Image Sensors. AICAS (2024)
Marius Bock, Michael Moeller, Kristof Van Laerhoven, Hilde Kuehne
WEAR: A Multimodal Dataset for Wearable and Egocentric Video Activity Recognition. CoRR (2023)
Harshil Bhatia, Edith Tretschk, Zorah Lähner, Marcel Seelbach Benkner, Michael Moeller, Christian Theobalt, Vladislav Golyanik
CCuantuMM: Cycle-Consistent Quantum-Hybrid Matching of Multiple Shapes. CVPR (2023)
Hannah Dröge, Zorah Lähner, Yuval Bahat, Onofre Martorell Nadal, Felix Heide, Michael Moeller
Kissing to Find a Match: Efficient Low-Rank Permutation Representation. NeurIPS (2023)
Jovita Lukasik, Michael Moeller, Margret Keuper
An Evaluation of Zero-Cost Proxies - From Neural Architecture Performance Prediction to Model Robustness. DAGM (2023)
Harshil Bhatia, Edith Tretschk, Zorah Lähner, Marcel Seelbach Benkner, Michael Moeller, Christian Theobalt, Vladislav Golyanik
CCuantuMM: Cycle-Consistent Quantum-Hybrid Matching of Multiple Shapes. CoRR (2023)
Marcel Seelbach Benkner, Maximilian Krahn, Edith Tretschk, Zorah Lähner, Michael Moeller, Vladislav Golyanik
QuAnt: Quantum Annealing with Learnt Couplings. ICLR (2023)
Zorah Lähner, Michael Moeller
On the Direct Alignment of Latent Spaces. UniReps (2023)
Hendrik Sommerhoff, Shashank Agnihotri, Mohamed Saleh, Michael Moeller, Margret Keuper, Andreas Kolb
Differentiable Sensor Layouts for End-to-End Learning of Task-Specific Camera Parameters. CoRR (2023)
Jonas Geiping, Micah Goldblum, Phillip Pope, Michael Moeller, Tom Goldstein
Stochastic Training is Not Necessary for Generalization. ICLR (2022)
Kanchana Vaishnavi Gandikota, Paramanand Chandramouli, Michael Moeller
On Adversarial Robustness of Deep Image Deblurring. CoRR (2022)
Marcel Seelbach Benkner, Maximilian Krahn, Edith Tretschk, Zorah Lähner, Michael Moeller, Vladislav Golyanik
QuAnt: Quantum Annealing with Learnt Couplings. CoRR (2022)
Samira Kabri, Alexander Auras, Danilo Riccio, Hartmut Bauermeister, Martin Benning, Michael Moeller, Martin Burger
Convergent Data-driven Regularizations for CT Reconstruction. CoRR (2022)
Hannah Dröge, Yuval Bahat, Felix Heide, Michael Moeller
Explorable Data Consistent CT Reconstruction. BMVC (2022)
Jonas Geiping, Liam H. Fowl, W. Ronny Huang, Wojciech Czaja, Gavin Taylor, Michael Moeller, Tom Goldstein
Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching. ICLR (2021)
Jonas Geiping, Micah Goldblum, Phillip E. Pope, Michael Moeller, Tom Goldstein
Stochastic Training is Not Necessary for Generalization. CoRR (2021)
Marius Bock, Alexander Hölzemann, Michael Moeller, Kristof Van Laerhoven
Improving Deep Learning for HAR with shallow LSTMs. CoRR (2021)
Jonas Geiping, Jovita Lukasik, Margret Keuper, Michael Moeller
DARTS for Inverse Problems: a Study on Hyperparameter Sensitivity. CoRR (2021)
Jonas Geiping, Liam Fowl, Gowthami Somepalli, Micah Goldblum, Michael Moeller, Tom Goldstein
What Doesn't Kill You Makes You Robust(er): Adversarial Training against Poisons and Backdoors. CoRR (2021)
Marcel Seelbach Benkner, Zorah Lähner, Vladislav Golyanik, Christof Wunderlich, Christian Theobalt, Michael Moeller
Q-Match: Iterative Shape Matching via Quantum Annealing. ICCV (2021)
Marcel Seelbach Benkner, Vladislav Golyanik, Christian Theobalt, Michael Moeller
Adiabatic Quantum Graph Matching with Permutation Matrix Constraints. CoRR (2021)
Marius Bock, Alexander Hölzemann, Michael Moeller, Kristof Van Laerhoven
Improving Deep Learning for HAR with Shallow LSTMs. ISWC (2021)
Jonas Geiping, Fjedor Gaede, Hartmut Bauermeister, Michael Moeller
Fast Convex Relaxations using Graph Discretizations. CoRR (2020)
Micah Goldblum, Jonas Geiping, Avi Schwarzschild, Michael Moeller, Tom Goldstein
Truth or backpropaganda? An empirical investigation of deep learning theory. ICLR (2020)
Marcel Seelbach Benkner, Vladislav Golyanik, Christian Theobalt, Michael Moeller
Adiabatic Quantum Graph Matching with Permutation Matrix Constraints. 3DV (2020)
Jonas Geiping, Hartmut Bauermeister, Hannah Dröge, Michael Moeller
Inverting Gradients - How easy is it to break privacy in federated learning? NeurIPS (2020)
Jonas Geiping, Hartmut Bauermeister, Hannah Dröge, Michael Moeller
Inverting Gradients - How easy is it to break privacy in federated learning? CoRR (2020)
Guruprasad M. Hegde, Avinash Nittur Ramesh, Kanchana Vaishnavi Gandikota, Roman Obermaisser, Michael Moeller
A Simple Domain Shifting Network for Generating Low Quality Images. ICPR (2020)
Guruprasad M. Hegde, Avinash Nittur Ramesh, Kanchana Vaishnavi Gandikota, Roman Obermaisser, Michael Moeller
A Simple Domain Shifting Network for Generating Low Quality Images. CoRR (2020)
Jonas Geiping, Fjedor Gaede, Hartmut Bauermeister, Michael Moeller
Fast Convex Relaxations using Graph Discretizations. BMVC (2020)
Jonas Geiping, Liam Fowl, W. Ronny Huang, Wojciech Czaja, Gavin Taylor, Michael Moeller, Tom Goldstein
Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching. CoRR (2020)
Paramanand Chandramouli, Kanchana Vaishnavi Gandikota, Andreas Görlitz, Andreas Kolb, Michael Moeller
Generative Models for Generic Light Field Reconstruction. CoRR (2020)
Christina Runkel, Stefan Dorenkamp, Hartmut Bauermeister, Michael Moeller
Exploiting the Logits: Joint Sign Language Recognition and Spell-Correction. CoRR (2020)
Micah Goldblum, Jonas Geiping, Avi Schwarzschild, Michael Moeller, Tom Goldstein
Truth or Backpropaganda? An Empirical Investigation of Deep Learning Theory. CoRR (2019)
Jonas Geiping, Michael Moeller
Parametric Majorization for Data-Driven Energy Minimization Methods. CoRR (2019)
Jonas Geiping, Michael Moeller
Parametric Majorization for Data-Driven Energy Minimization Methods. ICCV (2019)
Rania Briq, Michael Moeller, Juergen Gall
Convolutional Simplex Projection Network (CSPN) for Weakly Supervised Semantic Segmentation. CoRR (2018)
Michael Moeller, Otmar Loffeld, Juergen Gall, Felix Krahmer
Are good local minima wide in sparse recovery? CoRR (2018)
Rania Briq, Michael Moeller, Jürgen Gall
Convolutional Simplex Projection Network for Weakly Supervised Semantic Segmentation. BMVC (2018)