Winfried Ripken
Winfried Ripken
Sonstige NamenWinfried Lötzsch
Bestätigte E-Mail-Adresse bei - Startseite
Zitiert von
Zitiert von
3D Self-Supervised Methods for Medical Imaging
A Taleb, W Loetzsch, N Danz, J Severin, T Gaertner, B Bergner, C Lippert
Proceedings of NeurIPS 2020, 2020
Who wrote the web? Revisiting influential author identification research applicable to information retrieval
M Potthast, S Braun, T Buz, F Duffhauss, F Friedrich, JM Gülzow, J Köhler, ...
Advances in Information Retrieval: 38th European Conference on IR Research …, 2016
Learning the Solution Operator of Boundary Value Problems using Graph Neural Networks
W Lötzsch, S Ohler, J Otterbach
ICML 2022 2nd AI for Science Workshop, 2022
Using Deep Reinforcement Learning for the Continuous Control of Robotic Arms
W Lötzsch
Bachelor Thesis, 2018
WISE: Whitebox Image Stylization by Example-Based Learning
W Lötzsch, M Reimann, M Büssemeyer, A Semmo, J Döllner, M Trapp
European Conference on Computer Vision (ECCV), 135-152, 2022
Enhancing Multi-Objective Optimization through Machine Learning-Supported Multiphysics Simulation
D Botache, J Decke, W Ripken, A Dornipati, F Götz-Hahn, M Ayeb, B Sick
Proceedings of ECML 2024, 2023
Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive Models
J Siems*, K Ditschuneit*, W Ripken*, A Lindborg*, M Schambach, ...
Proceedings of NeurIPS 2023, 2023
Multiscale Neural Operators for Solving Time-Independent PDEs
W Ripken*, L Coiffard*, F Pieper*, S Dziadzio
The Symbiosis of Deep Learning and Differential Equations III, 2023
Towards Learning Self-Organized Criticality of Rydberg Atoms using Graph Neural Networks
S Ohler, DS Brady, W Lötzsch, M Fleischhauer, J Otterbach
ICML 2022 2nd AI for Science Workshop, 0
Simulating the Temperature-Dependent Absorbing-State Phase Transition in a Rydberg Many-Body Facilitated Gas using Neural Networks
S Ohler, D Brady, W Ripken, M Fleischhauer, J Otterbach
APS Division of Atomic, Molecular and Optical Physics Meeting Abstracts 2023 …, 2023
Learning languages with decidable hypotheses
J Berger, M Böther, V Doskoč, JG Harder, N Klodt, T Kötzing, W Lötzsch, ...
Connecting with Computability: 17th Conference on Computability in Europe …, 2021
Maps for Learning Indexable Classes
J Berger, M Böther, V Doskoč, JG Harder, N Klodt, T Kötzing, W Lötzsch, ...
arXiv preprint arXiv:2010.09460, 2020
Training a deep policy gradient-based neural network with asynchronous learners on a simulated robotic problem
W Lötzsch, J Vitay, F Hamker
INFORMATIK 2017, 2017
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–13