Michael Moeller

research

∙ 03/15/2022

Intrinsic Neural Fields: Learning Functions on Manifolds

Neural fields have gained significant attention in the computer vision c...

Lukas Koestler, et al. ∙

research

∙ 10/13/2021

Tutorial on Deep Learning for Human Activity Recognition

Activity recognition systems that are capable of estimating human activi...

Marius Bock, et al. ∙

research

∙ 09/29/2021

Stochastic Training is Not Necessary for Generalization

It is widely believed that the implicit regularization of stochastic gra...

Jonas Geiping, et al. ∙

research

∙ 08/12/2021

DARTS for Inverse Problems: a Study on Hyperparameter Sensitivity

Differentiable architecture search (DARTS) is a widely researched tool f...

Jonas Geiping, et al. ∙

research

∙ 08/02/2021

Improving Deep Learning for HAR with shallow LSTMs

Recent studies in Human Activity Recognition (HAR) have shown that Deep ...

Marius Bock, et al. ∙

research

∙ 07/13/2021

Lifting the Convex Conjugate in Lagrangian Relaxations: A Tractable Approach for Continuous Markov Random Fields

Dual decomposition approaches in nonconvex optimization may suffer from ...

Hartmut Bauermeister, et al. ∙

research

∙ 07/08/2021

Adiabatic Quantum Graph Matching with Permutation Matrix Constraints

Matching problems on 3D shapes and images are challenging as they are fr...

Marcel Seelbach Benkner, et al. ∙

research

∙ 06/18/2021

Training or Architecture? How to Incorporate Invariance in Neural Networks

Many applications require the robustness, or ideally the invariance, of ...

Kanchana Vaishnavi Gandikota, et al. ∙

research

∙ 05/06/2021

Q-Match: Iterative Shape Matching via Quantum Annealing

Finding shape correspondences can be formulated as an NP-hard quadratic ...

Marcel Seelbach Benkner, et al. ∙

research

∙ 02/26/2021

What Doesn't Kill You Makes You Robust(er): Adversarial Training against Poisons and Backdoors

Data poisoning is a threat model in which a malicious actor tampers with...

Jonas Geiping, et al. ∙

research

∙ 09/07/2020

Nonlinear Spectral Geometry Processing via the TV Transform

We introduce a novel computational framework for digital geometry proces...

Marco Fumero, et al. ∙

research

∙ 09/04/2020

Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching

Data Poisoning attacks involve an attacker modifying training data to ma...

Jonas Geiping, et al. ∙

research

∙ 07/01/2020

Exploiting the Logits: Joint Sign Language Recognition and Spell-Correction

Machine learning techniques have excelled in the automatic semantic anal...

Christina Runkel, et al. ∙

research

∙ 06/30/2020

A Simple Domain Shifting Networkfor Generating Low Quality Images

Deep Learning systems have proven to be extremely successful for image r...

Guruprasad Hegde, et al. ∙

research

∙ 05/13/2020

Generative Models for Generic Light Field Reconstruction

Recently deep generative models have achieved impressive progress in mod...

Paramanand Chandramouli, et al. ∙

research

∙ 04/23/2020

Fast Convex Relaxations using Graph Discretizations

Matching and partitioning problems are fundamentals of computer vision a...

Jonas Geiping, et al. ∙

research

∙ 03/31/2020

Inverting Gradients – How easy is it to break privacy in federated learning?

The idea of federated learning is to collaboratively train a neural netw...

Jonas Geiping, et al. ∙

research

∙ 10/01/2019

Truth or Backpropaganda? An Empirical Investigation of Deep Learning Theory

We empirically evaluate common assumptions about neural networks that ar...

Micah Goldblum, et al. ∙

research

∙ 08/17/2019

Parametric Majorization for Data-Driven Energy Minimization Methods

Energy minimization methods are a classical tool in a multitude of compu...

Jonas Geiping, et al. ∙

research

∙ 04/05/2019

Controlling Neural Networks via Energy Dissipation

The last decade has shown a tremendous success in solving various comput...

Michael Moeller, et al. ∙

research

∙ 07/24/2018

Convolutional Simplex Projection Network (CSPN) for Weakly Supervised Semantic Segmentation

Weakly supervised semantic segmentation has been a subject of increased ...

Rania Briq, et al. ∙

research

∙ 06/21/2018

Are good local minima wide in sparse recovery?

The idea of compressed sensing is to exploit representations in suitable...

Michael Moeller, et al. ∙

research

∙ 03/23/2018

Lifting Layers: Analysis and Applications

The great advances of learning-based approaches in image processing and ...

Peter Ochs, et al. ∙

research

∙ 02/20/2018

Composite Optimization by Nonconvex Majorization-Minimization

Many tasks in imaging can be modeled via the minimization of a nonconvex...

Jonas Geiping, et al. ∙

research

∙ 11/29/2017

Tighter Lifting-Free Convex Relaxations for Quadratic Matching Problems

In this work we study convex relaxations of quadratic optimisation probl...

Florian Bernard, et al. ∙

research

∙ 04/11/2017

Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems

While variational methods have been among the most powerful tools for so...

Tim Meinhardt, et al. ∙

research

∙ 11/23/2016

Multiframe Motion Coupling for Video Super Resolution

The idea of video super resolution is to use different view points of a ...

Jonas Geiping, et al. ∙

research

∙ 04/07/2016

Sublabel-Accurate Convex Relaxation of Vectorial Multilabel Energies

Convex relaxations of nonconvex multilabel problems have been demonstrat...

Emanuel Laude, et al. ∙

research

∙ 12/04/2015

Sublabel-Accurate Relaxation of Nonconvex Energies

We propose a novel spatially continuous framework for convex relaxations...

Thomas Möllenhoff, et al. ∙

research

∙ 10/05/2015

Nonlinear Spectral Analysis via One-homogeneous Functionals - Overview and Future Prospects

We present in this paper the motivation and theory of nonlinear spectral...

Guy Gilboa, et al. ∙

research

∙ 06/18/2015

Point-wise Map Recovery and Refinement from Functional Correspondence

Since their introduction in the shape analysis community, functional map...

Emanuele Rodolà, et al. ∙

research

∙ 08/01/2014

Variational Depth from Focus Reconstruction

This paper deals with the problem of reconstructing a depth map from a s...

Michael Moeller, et al. ∙

research

∙ 07/07/2014

The Primal-Dual Hybrid Gradient Method for Semiconvex Splittings

This paper deals with the analysis of a recent reformulation of the prim...

Thomas Möllenhoff, et al. ∙

Michael Moeller

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