Michael Moeller
21 papers · 2015–2026 · 7 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (35) 🏃 Academic Marathon · Half 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird
🧬
Topic Evolution
🧭
Keyword Pioneer
🏆
Keyword Champion
(2)
🌈
Renaissance Researcher
(5)
🔥
Unstoppable · Bronze
❓
The Questioner
(2)
⚡
Prolific Year · Productive
🚀
Conference Pioneer
💎
Century Club · Bronze
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Keyword Collector
(90)
Top co-authors
Research topics
Machine Learning
(14)
Computer Vision
(10)
Optimization & Theory
(10)
Mathematics & Optimization
(7)
Optimization
(7)
Processing
(6)
Artificial Intelligence
(5)
Deep Learning
(5)
Analysis
(4)
Core AI · Artificial Intelligence
(4)
Core AI · Computer Vision
(3)
Mathematics
(3)
Application Areas
(2)
Architectures
(2)
Core Methods
(2)
Keywords
combinatorial optimization
(4)
quantum annealing
(4)
shape matching
(3)
image reconstruction
(3)
energy minimization
(2)
graph matching
(2)
neural network
(2)
permutation matrix
(2)
quadratic unconstrained binary optimization
(2)
adversarial attack
(2)
adversarial robustness
(1)
point set registration
(1)
non-rigid matching
(1)
analog-to-digital conversion
(1)
matrix factorization
(1)
iterative optimization
(1)
neural tangent kernel
(1)
convex optimization
(1)
semidefinite programming
(1)
stochastic gradient descent
(1)
Papers
A Bit is All You Need! Efficient Video Capture via Single Bit Imaging
CVPR 2026
QuCOOP: A Versatile Framework for Solving Composite and Binary-Parametrised Problems on Quantum Annealers
CVPR 2025
Implicit Representations for Constrained Image Segmentation
ICML 2024
CCuantuMM: Cycle-Consistent Quantum-Hybrid Matching of Multiple Shapes
CVPR 2023
Evaluating Adversarial Robustness of Low dose CT Recovery
MIDL 2023
Kissing to Find a Match: Efficient Low-Rank Permutation Representation
NeurIPS 2023
QuAnt: Quantum Annealing with Learnt Couplings
ICLR 2023
SIGMA: Scale-Invariant Global Sparse Shape Matching
ICCV 2023
Intrinsic Neural Fields: Learning Functions on Manifolds
ECCV 2022
Stochastic Training is Not Necessary for Generalization
ICLR 2022
Q-Match: Iterative Shape Matching via Quantum Annealing
ICCV 2021
Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching
ICLR 2021
Inverting Gradients - How easy is it to break privacy in federated learning?
NeurIPS 2020
Truth or backpropaganda? An empirical investigation of deep learning theory
ICLR 2020
Controlling Neural Networks via Energy Dissipation
ICCV 2019
Parametric Majorization for Data-Driven Energy Minimization Methods
ICCV 2019
DS*: Tighter Lifting-Free Convex Relaxations for Quadratic Matching Problems
CVPR 2018
Lifting Layers: Analysis and Applications
ECCV 2018
Proximal Backpropagation
ICLR 2018
Sublabel-Accurate Relaxation of Nonconvex Energies
CVPR 2016
Learning Nonlinear Spectral Filters for Color Image Reconstruction
ICCV 2015