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 | 260 | 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 | 198 | 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 | 142 | 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 | 138 | 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 | 112 | 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 | 102 | 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 | 67 | 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 | 48 | 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 | 43 | 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 | 38 | 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 | 18 | 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 | 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 International Conference on Learning Representations (ICLR), 2024 | 12* | 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 | 12 | 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 | 12 | 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 | 10 | 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 | 9 | 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 |
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 | 5 | 2023 |