Mundt, Martin

16 publications

ICLRW 2025 Federated Circuits: A Unified Framework for Scalable and Efficient Federated Learning Jonas Seng, Florian Peter Busch, Pooja Prasad, Devendra Singh Dhami, Martin Mundt, Kristian Kersting

UAI 2025 Scaling Probabilistic Circuits via Data Partitioning Jonas Seng, Florian Peter Busch, Pooja Prasad, Devendra Singh Dhami, Martin Mundt, Kristian Kersting

TMLR 2025 Tractable Representation Learning with Probabilistic Circuits Steven Braun, Sahil Sidheekh, Antonio Vergari, Martin Mundt, Sriraam Natarajan, Kristian Kersting

ICML 2025 Where Is the Truth? the Risk of Getting Confounded in a Continual World Florian Peter Busch, Roshni Ramanna Kamath, Rupert Mitchell, Wolfgang Stammer, Kristian Kersting, Martin Mundt

ICLR 2024 Adaptive Rational Activations to Boost Deep Reinforcement Learning Quentin Delfosse, Patrick Schramowski, Martin Mundt, Alejandro Molina, Kristian Kersting

TMLR 2024 Continual Learning: Applications and the Road Forward 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

AISTATS 2024 Deep Classifier Mimicry Without Data Access Steven Braun, Martin Mundt, Kristian Kersting

WACV 2024 Designing a Hybrid Neural System to Learn Real-World Crack Segmentation from Fractal-Based Simulation Achref Jaziri, Martin Mundt, Andres Fernandez, Visvanathan Ramesh

CoLLAs 2024 Masked Autoencoders Are Efficient Continual Federated Learners Subarnaduti Paul, Lars-Joel Frey, Roshni Ramanna Kamath, Kristian Kersting, Martin Mundt

UAI 2023 Probabilistic Circuits That Know What They Don’t Know Fabrizio Ventola, Steven Braun, Zhongjie Yu, Martin Mundt, Kristian Kersting

ICLR 2022 CLEVA-Compass: A Continual Learning Evaluation Assessment Compass to Promote Research Transparency and Comparability Martin Mundt, Steven Lang, Quentin Delfosse, Kristian Kersting

UAI 2022 Predictive Whittle Networks for Time Series Zhongjie Yu, Fabrizio Ventola, Nils Thoma, Devendra Singh Dhami, Martin Mundt, Kristian Kersting

ECCV 2022 When Deep Classifiers Agree: Analyzing Correlations Between Learning Order and Image Statistics Iuliia Pliushch, Martin Mundt, Nicolas Lupp, Visvanathan Ramesh

CVPRW 2021 Avalanche: An End-to-End Library for Continual Learning 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 W. 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

CVPRW 2021 Neural Architecture Search of Deep Priors: Towards Continual Learning Without Catastrophic Interference Martin Mundt, Iuliia Pliushch, Visvanathan Ramesh

ICCVW 2019 Open Set Recognition Through Deep Neural Network Uncertainty: Does Out-of-Distribution Detection Require Generative Classifiers? Martin Mundt, Iuliia Pliushch, Sagnik Majumder, Visvanathan Ramesh