Martin Mundt

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 48

Top Topics

Virtual Reality

Neural Architecture

Top Venues

Neural Networks

Publications

Achref Jaziri, Martin Mundt, Andres Fernandez Rodriguez, Visvanathan Ramesh
Designing a Hybrid Neural System to Learn Real-world Crack Segmentation from Fractal-based Simulation. WACV (2024)
Quentin Delfosse, Patrick Schramowski, Martin Mundt, Alejandro Molina, Kristian Kersting
Adaptive Rational Activations to Boost Deep Reinforcement Learning. ICLR (2024)
Roshni Kamath, Rupert Mitchell, Subarnaduti Paul, Kristian Kersting, Martin Mundt
BOWLL: A Deceptively Simple Open World Lifelong Learner. CoRR (2024)
Nick Lemke, Camila González, Anirban Mukhopadhyay, Martin Mundt
Distribution-Aware Replay for Continual MRI Segmentation. CoRR (2024)
Eli Verwimp, Rahaf Aljundi, Shai Ben-David, Matthias Bethge, Andrea Cossu, Alexander Gepperth, Tyler L. Hayes, Eyke Hüllermeier, Christopher Kanan, Dhireesha Kudithipudi, Christoph H. Lampert, Martin Mundt, Razvan Pascanu, Adrian Popescu, Andreas S. Tolias, Joost van de Weijer, Bing Liu, Vincenzo Lomonaco, Tinne Tuytelaars, Gido M. van de Ven
Continual Learning: Applications and the Road Forward. Trans. Mach. Learn. Res. 2024 (2024)
Steven Braun, Martin Mundt, Kristian Kersting
Deep Classifier Mimicry without Data Access. AISTATS (2024)
Florian Peter Busch, Roshni Kamath, Rupert Mitchell, Wolfgang Stammer, Kristian Kersting, Martin Mundt
Where is the Truth? The Risk of Getting Confounded in a Continual World. CoRR (2024)
Eli Verwimp, Shai Ben-David, Matthias Bethge, Andrea Cossu, Alexander Gepperth, Tyler L. Hayes, Eyke Hüllermeier, Christopher Kanan, Dhireesha Kudithipudi, Christoph H. Lampert, Martin Mundt, Razvan Pascanu, Adrian Popescu, Andreas S. Tolias, Joost van de Weijer, Bing Liu, Vincenzo Lomonaco, Tinne Tuytelaars, Gido M. van de Ven
Continual Learning: Applications and the Road Forward. CoRR (2023)
Martin Mundt, Yongwon Hong, Iuliia Pliushch, Visvanathan Ramesh
A wholistic view of continual learning with deep neural networks: Forgotten lessons and the bridge to active and open world learning. Neural Networks 160 (2023)
Fabrizio Ventola, Steven Braun, Zhongjie Yu, Martin Mundt, Kristian Kersting
Probabilistic Circuits That Know What They Don't Know. CoRR (2023)
Steven Braun, Martin Mundt, Kristian Kersting
Deep Classifier Mimicry without Data Access. CoRR (2023)
Adrian Lutsch, Gagandeep Singh, Martin Mundt, Ragnar Mogk, Carsten Binnig
Benchmarking the Second Generation of Intel SGX for Machine Learning Workloads. BTW (2023)
Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J. Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi Jethwani, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx McLean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J. Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y. Bilenko, Andrew McNamara, Raphael Gontijo Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, Luke Stark
Queer In AI: A Case Study in Community-Led Participatory AI. FAccT (2023)
Rupert Mitchell, Martin Mundt, Kristian Kersting
Self Expanding Neural Networks. CoRR (2023)
Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J. Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi Jethwani, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx McLean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J. Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y. Bilenko, Andrew McNamara, Raphael Gontijo Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, Luke Stark
Queer In AI: A Case Study in Community-Led Participatory AI. CoRR (2023)
Fabrizio Ventola, Steven Braun, Zhongjie Yu, Martin Mundt, Kristian Kersting
Probabilistic circuits that know what they don't know. UAI (2023)
Martin Mundt, Keiland W. Cooper, Devendra Singh Dhami, Adèle H. Ribeiro, James Seale Smith, Alexis Bellot, Tyler L. Hayes
Continual Causality: A Retrospective of the Inaugural AAAI-23 Bridge Program. AAAI Bridge Program (2023)
Achref Jaziri, Martin Mundt, Andres Fernandez Rodriguez, Visvanathan Ramesh
Designing a Hybrid Neural System to Learn Real-world Crack Segmentation from Fractal-based Simulation. CoRR (2023)
Subarnaduti Paul, Lars-Joel Frey, Roshni Kamath, Kristian Kersting, Martin Mundt
Masked Autoencoders are Efficient Continual Federated Learners. CoRR (2023)
Zhongjie Yu, Fabrizio Ventola, Nils Thoma, Devendra Singh Dhami, Martin Mundt, Kristian Kersting
Predictive Whittle networks for time series. UAI (2022)
Yongwon Hong, Martin Mundt, Sungho Park, Yungjung Uh, Hyeran Byun
Return of the normal distribution: Flexible deep continual learning with variational auto-encoders. Neural Networks 154 (2022)
Mara Kaufeld, Martin Mundt, Sarah Forst, Heiko Hecht
Optical see-through augmented reality can induce severe motion sickness. Displays 74 (2022)
Martin Mundt, Iuliia Pliushch, Sagnik Majumder, Yong Won Hong, Visvanathan Ramesh
Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition. J. Imaging 8 (4) (2022)
Martin Mundt, Steven Lang, Quentin Delfosse, Kristian Kersting
CLEVA-Compass: A Continual Learning Evaluation Assessment Compass to Promote Research Transparency and Comparability. ICLR (2022)
Iuliia Pliushch, Martin Mundt, Nicolas Lupp, Visvanathan Ramesh
When Deep Classifiers Agree: Analyzing Correlations Between Learning Order and Image Statistics. ECCV (8) (2022)
Timm Hess, Martin Mundt, Iuliia Pliushch, Visvanathan Ramesh
A Procedural World Generation Framework for Systematic Evaluation of Continual Learning. CoRR (2021)
Martin Mundt, Iuliia Pliushch, Visvanathan Ramesh
Neural Architecture Search of Deep Priors: Towards Continual Learning without Catastrophic Interference. CoRR (2021)
Vincenzo Lomonaco, Lorenzo Pellegrini, Andrea Cossu, Antonio Carta, Gabriele Graffieti, Tyler L. Hayes, Matthias De Lange, Marc Masana, Jary Pomponi, Gido M. van de Ven, Martin Mundt, Qi She, Keiland Cooper, Jeremy Forest, Eden Belouadah, Simone Calderara, German Ignacio Parisi, Fabio Cuzzolin, Andreas S. Tolias, Simone Scardapane, Luca Antiga, Subutai Ahmad, Adrian Popescu, Christopher Kanan, Joost van de Weijer, Tinne Tuytelaars, Davide Bacciu, Davide Maltoni
Avalanche: An End-to-End Library for Continual Learning. CVPR Workshops (2021)
Martin Mundt, Iuliia Pliushch, Visvanathan Ramesh
Neural Architecture Search of Deep Priors: Towards Continual Learning Without Catastrophic Interference. CVPR Workshops (2021)
Steven Lang, Martin Mundt, Fabrizio Ventola, Robert Peharz, Kristian Kersting
Elevating Perceptual Sample Quality in PCs through Differentiable Sampling. Pre-Registration Workshop @ NeurIPS (2021)
Timm Hess, Martin Mundt, Iuliia Pliushch, Visvanathan Ramesh
A Procedural World Generation Framework for Systematic Evaluation of Continual Learning. NeurIPS Datasets and Benchmarks (2021)
Martin Mundt, Steven Lang, Quentin Delfosse, Kristian Kersting
CLEVA-Compass: A Continual Learning EValuation Assessment Compass to Promote Research Transparency and Comparability. CoRR (2021)
Iuliia Pliushch, Martin Mundt, Nicolas Lupp, Visvanathan Ramesh
When Deep Classifiers Agree: Analyzing Correlations between Learning Order and Image Statistics. CoRR (2021)
Vincenzo Lomonaco, Lorenzo Pellegrini, Andrea Cossu, Antonio Carta, Gabriele Graffieti, Tyler L. Hayes, Matthias De Lange, Marc Masana, Jary Pomponi, Gido M. van de Ven, Martin Mundt, Qi She, Keiland Cooper, Jeremy Forest, Eden Belouadah, Simone Calderara, German Ignacio Parisi, Fabio Cuzzolin, Andreas S. Tolias, Simone Scardapane, Luca Antiga, Subutai Amhad, Adrian Popescu, Christopher Kanan, Joost van de Weijer, Tinne Tuytelaars, Davide Bacciu, Davide Maltoni
Avalanche: an End-to-End Library for Continual Learning. CoRR (2021)
Martin Mundt, Yong Won Hong, Iuliia Pliushch, Visvanathan Ramesh
A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning. CoRR (2020)
Martin Mundt, Tintu Mathew
An Evaluation of Pie Menus for System Control in Virtual Reality. NordiCHI (2020)
Martin Mundt, Sagnik Majumder, Sreenivas Murali, Panagiotis Panetsos, Visvanathan Ramesh
Meta-learning Convolutional Neural Architectures for Multi-target Concrete Defect Classification with the COncrete DEfect BRidge IMage Dataset. CoRR (2019)
Martin Mundt, Iuliia Pliushch, Sagnik Majumder, Visvanathan Ramesh
Open Set Recognition Through Deep Neural Network Uncertainty: Does Out-of-Distribution Detection Require Generative Classifiers? ICCV Workshops (2019)
Martin Mundt, Sagnik Majumder, Sreenivas Murali, Panagiotis Panetsos, Visvanathan Ramesh
Meta-Learning Convolutional Neural Architectures for Multi-Target Concrete Defect Classification With the COncrete DEfect BRidge IMage Dataset. CVPR (2019)
Martin Mundt, Sagnik Majumder, Iuliia Pliushch, Visvanathan Ramesh
Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition. CoRR (2019)
Martin Mundt, Tintu Mathew
Exploring Pie Menus for System Control Tasks in Virtual Reality. Mensch & Computer (2019)
Martin Mundt, Iuliia Pliushch, Sagnik Majumder, Visvanathan Ramesh
Open Set Recognition Through Deep Neural Network Uncertainty: Does Out-of-Distribution Detection Require Generative Classifiers? CoRR (2019)
Martin Mundt, Sagnik Majumder, Tobias Weis, Visvanathan Ramesh
Rethinking Layer-wise Feature Amounts in Convolutional Neural Network Architectures. CoRR (2018)
Martin Mundt, Tobias Weis, Kishore Konda, Visvanathan Ramesh
Building effective deep neural network architectures one feature at a time. CoRR (2017)
Helge Fischer, Matthias Heinz, Christian Leyh, Marko Ott, Sandra Döring, Cornelia Schade, Annika Löser, Martin Mundt, Anne Trojanek, Holger Rohland
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). DeLFI/GMW Workshops (2017)
Timm Hess, Martin Mundt, Tobias Weis, Visvanathan Ramesh
Large-Scale Stochastic Scene Generation and Semantic Annotation for Deep Convolutional Neural Network Training in the RoboCup SPL. RoboCup (2017)
Tobias Weis, Martin Mundt, Patrick Harding, Visvanathan Ramesh
Anomaly detection for automotive visual signal transition estimation. ITSC (2017)
Martin Mundt, Sebastian Blaes, Thomas Burwick
Feature binding in deep convolution networks with recurrences, oscillations, and top-down modulated dynamics. ESANN (2016)