Martin Mundt
Martin Mundt
Independent Research Group Leader at TU Darmstadt & hessian.AI, Board at ContinualAI
Verified email at - Homepage
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CMOS integrated antenna-coupled field-effect transistors for the detection of radiation from 0.2 to 4.3 THz
S Boppel, A Lisauskas, M Mundt, D Seliuta, L Minkevicius, I Kasalynas, ...
IEEE transactions on microwave theory and techniques 60 (12), 3834-3843, 2012
Avalanche: an end-to-end library for continual learning
V Lomonaco, L Pellegrini, A Cossu, A Carta, G Graffieti, TL Hayes, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
Meta-learning Convolutional Neural Architectures for Multi-target Concrete Defect Classification with the COncrete DEfect BRidge IMage Dataset
M Mundt, S Majumder, S Murali, P Panetsos, V Ramesh
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019
A wholistic view of continual learning with deep neural networks: Forgotten lessons and the bridge to active and open world learning
M Mundt, Y Hong, I Pliushch, V Ramesh
Neural Networks 160, 306-336, 2023
Exploration of terahertz imaging with silicon MOSFETs
A Lisauskas, M Bauer, S Boppel, M Mundt, B Khamaisi, E Socher, ...
Journal of Infrared, Millimeter, and Terahertz Waves 35, 63-80, 2014
Antenna-coupled field-effect transistors for multi-spectral terahertz imaging up to 4.25 THz
M Bauer, R Venckevičius, I Kašalynas, S Boppel, M Mundt, L Minkevičius, ...
Optics express 22 (16), 19235-19241, 2014
Subharmonic Mixing With Field-Effect Transistors: Theory and Experiment at 639 GHz High Above
A Lisauskas, S Boppel, M Mundt, V Krozer, HG Roskos
IEEE Sensors Journal 13 (1), 124-132, 2012
Open Set Recognition Through Deep Neural Network Uncertainty: Does Out-of-Distribution Detection Require Generative Classifiers?
M Mundt, I Pliushch, S Majumder, V Ramesh
International Conference on Computer Vision (ICCV) 2019, Workshop on …, 2019
Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition
M Mundt, I Pliushch, S Majumder, Y Hong, V Ramesh
Journal of Imaging, Special Issue Continual Learning in Computer Vision …, 2022
CLEVA-Compass: A Continual Learning EValuation Assessment Compass to Promote Research Transparency and Comparability
M Mundt, S Lang, Q Delfosse, K Kersting
International Conference on Learning Representations (ICLR), 2022
Queer in AI: A case study in community-led participatory AI
OO Queerinai, A Ovalle, A Subramonian, A Singh, C Voelcker, ...
Proceedings of the 2023 ACM Conference on Fairness, Accountability, and …, 2023
Large-scale Stochastic Scene Generation and Semantic Annotation for Deep Convolutional Neural Network Training in the RoboCup SPL
T Hess*, M Mundt*, T Weis, V Ramesh, (* equal contribution)
RoboCup 2017: Robot World CUP XXI, LNAI 11175, 2017
Bow-tie-antenna-coupled terahertz detectors using AlGaN/GaN field-effect transistors with 0.25 micrometer gate length
M Bauer, A Lisauskas, S Boppel, M Mundt, V Krozer, HG Roskos, ...
2013 European Microwave Integrated Circuit Conference, 212-215, 2013
Adaptive Rational Activations to Boost Deep Reinforcement Learning
Q Delfosse, P Schramowski, M Mundt, A Molina, K Kersting
International Conference on Learning Representations (ICLR), 2024
When deep classifiers agree: Analyzing correlations between learning order and image statistics
I Pliushch, M Mundt, N Lupp, V Ramesh
ECCV 2022: 17th European Conference on Computer Vision, Tel Aviv, Israel …, 2022
Anomaly Detection for Automotive Visual Signal Transition Estimation
T Weis, M Mundt, P Harding, V Ramesh
20th IEEE Intelligent Transportation Systems Conference (ITSC), 2017
Continual learning: Applications and the road forward
E Verwimp, S Ben-David, M Bethge, A Cossu, A Gepperth, TL Hayes, ...
Transactions on Machine Learning Research, 2024
Neural architecture search of deep priors: Towards continual learning without catastrophic interference
M Mundt, I Pliushch, V Ramesh
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
A Procedural World Generation Framework for Systematic Evaluation of Continual Learning
T Hess, M Mundt, I Pliushch, V Ramesh
Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track, 2021
Probabilistic Circuits That Know What They Don't Know
F Ventola, S Braun, Z Yu, M Mundt, K Kersting
Proceedings of the 39th Conference on Uncertainty in Artificial Intelligence …, 2023
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