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
255 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
179 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
125 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
124 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
110 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
101 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
66 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
46 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
42 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
32 2022 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
18 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
15 2013 Adaptive Rational Activations to Boost Deep Reinforcement Learning Q Delfosse, P Schramowski, M Mundt, A Molina, K Kersting
arXiv preprint arXiv:2102.09407, 2021
13 * 2021 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
11 2023 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
10 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
10 2017 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
7 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
6 2021 Optimized Tera-FET detector performance based on an analytical device model verified up to 9 THz S Boppel, A Lisauskas, M Bauer, M Mundt, R Venckevičius, L Minkevičius, ...
2013 38th International Conference on Infrared, Millimeter, and Terahertz …, 2013
6 2013 Return of the normal distribution: Flexible deep continual learning with variational auto-encoders Y Hong, M Mundt, S Park, Y Uh, H Byun
Neural Networks 154, 397-412, 2022
5 2022