Martin Mundt
Orcid: 0000-0003-1639-8255Affiliations:
- TU Darmstadt, Germany
According to our database1,
Martin Mundt
authored at least 37 papers
between 2016 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on owll-lab.com
-
on orcid.org
On csauthors.net:
Bibliography
2024
Designing a Hybrid Neural System to Learn Real-world Crack Segmentation from Fractal-based Simulation.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024
2023
A wholistic view of continual learning with deep neural networks: Forgotten lessons and the bridge to active and open world learning.
Neural Networks, March, 2023
Proceedings of the Uncertainty in Artificial Intelligence, 2023
Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023
Proceedings of the Datenbanksysteme für Business, 2023
Proceedings of the AAAI Bridge Program on Continual Causality, 2023
2022
Return of the normal distribution: Flexible deep continual learning with variational auto-encoders.
Neural Networks, 2022
Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition.
J. Imaging, 2022
Displays, 2022
Proceedings of the Uncertainty in Artificial Intelligence, 2022
CLEVA-Compass: A Continual Learning Evaluation Assessment Compass to Promote Research Transparency and Comparability.
Proceedings of the Tenth International Conference on Learning Representations, 2022
When Deep Classifiers Agree: Analyzing Correlations Between Learning Order and Image Statistics.
Proceedings of the Computer Vision - ECCV 2022, 2022
2021
PhD thesis, 2021
Proceedings of the NeurIPS 2021 Workshop on Pre-Registration in Machine Learning, 2021
A Procedural World Generation Framework for Systematic Evaluation of Continual Learning.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021
Neural Architecture Search of Deep Priors: Towards Continual Learning Without Catastrophic Interference.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021
2020
A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning.
CoRR, 2020
Proceedings of the NordiCHI '20: Shaping Experiences, 2020
2019
Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition.
CoRR, 2019
Proceedings of Mensch und Computer 2019, Hamburg, Germany, September 8-11, 2019, 2019
Open Set Recognition Through Deep Neural Network Uncertainty: Does Out-of-Distribution Detection Require Generative Classifiers?
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019
Meta-Learning Convolutional Neural Architectures for Multi-Target Concrete Defect Classification With the COncrete DEfect BRidge IMage Dataset.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019
2018
CoRR, 2018
2017
CoRR, 2017
Large-Scale Stochastic Scene Generation and Semantic Annotation for Deep Convolutional Neural Network Training in the RoboCup SPL.
Proceedings of the RoboCup 2017: Robot World Cup XXI [Nagoya, Japan, July 27-31, 2017]., 2017
Proceedings of the 20th IEEE International Conference on Intelligent Transportation Systems, 2017
Lernst du noch oder spielst du schon? Zum Einsatz von GameDesign-Elementen in der Hochschullehre.(Are you still Learning or Already Gaming? The Usage of Game Design Elements in University Teaching).
Proceedings of the Joint Proceedings of the Pre-Conference Workshops of DeLFI and GMW 2017 co-located with 15th e-Learning Conference of the German Computer Society (DeLFI 2017) and the 25th Annual Conference of the Gesellschaft für Medien in der Wissenschaft (GMW 2017), 2017
2016
Feature binding in deep convolution networks with recurrences, oscillations, and top-down modulated dynamics.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016