Martin Mundt - RankMe

68 papers A* 4A 5B 2C 1Misc 3Journal 36Unranked 13

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Modular Memory is the Key to Continual Learning Agents. CoRR Vaggelis Dorovatas, Malte Schwerin, Andrew D. Bagdanov, Lucas Caccia, Antonio Carta, Laurent Charlin, Barbara Hammer, Tyler L. Hayes, Timm Hess, Christopher Kanan, Dhireesha Kudithipudi, Xialei Liu, Vincenzo Lomonaco, Jorge Mendez-Mendez, Darshan Patil, Ameya Prabhu, Elisa Ricci, Tinne Tuytelaars, Gido M. van de Ven, Liyuan Wang, Joost van de Weijer, Jonghyun Choi, Martin Mundt, Rahaf Aljundi
2025	J	`jnl`	Beyond Binary Out-of-Distribution Detection: Characterizing Distributional Shifts with Multi-Statistic Diffusion Trajectories. CoRR Achref Jaziri, Martin Rogmann, Martin Mundt, Visvanathan Ramesh
2025	J	`jnl`	CHRONOBERG: Capturing Language Evolution and Temporal Awareness in Foundation Models. CoRR Niharika Hegde, Subarnaduti Paul, Lars-Joel Frey, Manuel Brack, Kristian Kersting, Martin Mundt, Patrick Schramowski
2025	J	`jnl`	Continual Learning Should Move Beyond Incremental Classification. CoRR Rupert Mitchell, Antonio Alliegro, Raffaello Camoriano, Dustin Carrión-Ojeda, Antonio Carta, Georgia Chalvatzaki, Nikhil Churamani, Carlo D'Eramo, Samin Hamidi, Robin Hesse, Fabian Hinder, Roshni Kamath, Vincenzo Lomonaco, Subarnaduti Paul, Francesca Pistilli, Tinne Tuytelaars, Gido M. van de Ven, Kristian Kersting, Simone Schaub-Meyer, Martin Mundt
2025	—	`conf`	Core Tokensets for Data-Efficient Sequential Training of Transformers. ICCVW Subarnaduti Paul, Manuel Brack, Patrick Schramowski, Kristian Kersting, Martin Mundt
2025	A	`conf`	Scaling Probabilistic Circuits via Data Partitioning. UAI Jonas Seng, Florian Peter Busch, Pooja Prasad, Devendra Singh Dhami, Martin Mundt, Kristian Kersting
2025	J	`jnl`	Scaling Probabilistic Circuits via Data Partitioning. CoRR Jonas Seng, Florian Peter Busch, Pooja Prasad, Devendra Singh Dhami, Martin Mundt, Kristian Kersting
2025	J	`jnl`	The Cake that is Intelligence and Who Gets to Bake it: An AI Analogy and its Implications for Participation. CoRR Martin Mundt, Anaelia Ovalle, Felix Friedrich, A Pranav, Subarnaduti Paul, Manuel Brack, Kristian Kersting, William Agnew
2025	B	`conf`	Three-Touch: A Manual Overlaying Technique for Augmented Content. SMC Martin Mundt, Johannes Klöckner, Leonie Seynsche, Tintu Mathew
2025	J	`jnl`	Tractable Representation Learning with Probabilistic Circuits. CoRR Steven Braun, Sahil Sidheekh, Antonio Vergari, Martin Mundt, Sriraam Natarajan, Kristian Kersting
2025	J	`jnl`	Tractable Representation Learning with Probabilistic Circuits. Trans. Mach. Learn. Res. Steven Braun, Sahil Sidheekh, Antonio Vergari, Martin Mundt, Sriraam Natarajan, Kristian Kersting
2025	A*	`conf`	Where is the Truth? The Risk of Getting Confounded in a Continual World. ICML Florian Peter Busch, Roshni Ramanna Kamath, Rupert Mitchell, Wolfgang Stammer, Kristian Kersting, Martin Mundt
2024	—	`ed.`	AAAI Bridge Program on Continual Causality, 20-21 February 2024, Vancouver, Canada. AAAI Bridge Program Martin Mundt, Keiland W. Cooper, Devendra Singh Dhami, Tyler L. Hayes, Rebecca Herman, Adéle Ribeiro, James Seale Smith
2024	A*	`conf`	Adaptive Rational Activations to Boost Deep Reinforcement Learning. ICLR Quentin Delfosse, Patrick Schramowski, Martin Mundt, Alejandro Molina, Kristian Kersting
2024	J	`jnl`	Aligning Generalisation Between Humans and Machines. CoRR Filip Ilievski, Barbara Hammer, Frank van Harmelen, Benjamin Paassen, Sascha Saralajew, Ute Schmid, Michael Biehl, Marianna Bolognesi, Xin Luna Dong, Kiril Gashteovski, Pascal Hitzler, Giuseppe Marra, Pasquale Minervini, Martin Mundt, Axel-Cyrille Ngonga Ngomo, Alessandro Oltramari, Gabriella Pasi, Zeynep G. Saribatur, Luciano Serafini, John Shawe-Taylor, Vered Shwartz, Gabriella Skitalinskaya, Clemens Stachl, Gido M. van de Ven, Thomas Villmann
2024	J	`jnl`	BOWLL: A Deceptively Simple Open World Lifelong Learner. CoRR Roshni Kamath, Rupert Mitchell, Subarnaduti Paul, Kristian Kersting, Martin Mundt
2024	J	`jnl`	Continual Learning: Applications and the Road Forward. Trans. Mach. Learn. Res. 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
2024	J	`jnl`	Core Tokensets for Data-efficient Sequential Training of Transformers. CoRR Subarnaduti Paul, Manuel Brack, Patrick Schramowski, Kristian Kersting, Martin Mundt
2024	A	`conf`	Deep Classifier Mimicry without Data Access. AISTATS Steven Braun, Martin Mundt, Kristian Kersting
2024	A	`conf`	Designing a Hybrid Neural System to Learn Real-world Crack Segmentation from Fractal-based Simulation. WACV Achref Jaziri, Martin Mundt, Andres Fernandez Rodriguez, Visvanathan Ramesh
2024	—	`conf`	Distribution-Aware Replay for Continual MRI Segmentation. AIPAD/PILM@MICCAI Nick Lemke, Camila González, Anirban Mukhopadhyay, Martin Mundt
2024	J	`jnl`	Distribution-Aware Replay for Continual MRI Segmentation. CoRR Nick Lemke, Camila González, Anirban Mukhopadhyay, Martin Mundt
2024	—	`conf`	Masked Autoencoders are Efficient Continual Federated Learners. CoLLAs Subarnaduti Paul, Lars-Joel Frey, Roshni Ramanna Kamath, Kristian Kersting, Martin Mundt
2024	J	`jnl`	Where is the Truth? The Risk of Getting Confounded in a Continual World. CoRR Florian Peter Busch, Roshni Kamath, Rupert Mitchell, Wolfgang Stammer, Kristian Kersting, Martin Mundt
2023	J	`jnl`	A wholistic view of continual learning with deep neural networks: Forgotten lessons and the bridge to active and open world learning. Neural Networks Martin Mundt, Yongwon Hong, Iuliia Pliushch, Visvanathan Ramesh
2023	—	`ed.`	AAAI Bridge Program on Continual Causality, 7-8 February 2023, Washington, DC, USA AAAI Bridge Program Martin Mundt, Keiland W. Cooper, Devendra Singh Dhami, Adèle H. Ribeiro, James Seale Smith, Alexis Bellot, Tyler L. Hayes
2023	Misc	`conf`	Benchmarking the Second Generation of Intel SGX for Machine Learning Workloads. BTW Adrian Lutsch, Gagandeep Singh, Martin Mundt, Ragnar Mogk, Carsten Binnig
2023	—	`conf`	Continual Causality: A Retrospective of the Inaugural AAAI-23 Bridge Program. AAAI Bridge Program Martin Mundt, Keiland W. Cooper, Devendra Singh Dhami, Adèle H. Ribeiro, James Seale Smith, Alexis Bellot, Tyler L. Hayes
2023	J	`jnl`	Continual Learning: Applications and the Road Forward. CoRR 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
2023	J	`jnl`	Deep Classifier Mimicry without Data Access. CoRR Steven Braun, Martin Mundt, Kristian Kersting
2023	J	`jnl`	Designing a Hybrid Neural System to Learn Real-world Crack Segmentation from Fractal-based Simulation. CoRR Achref Jaziri, Martin Mundt, Andres Fernandez Rodriguez, Visvanathan Ramesh
2023	J	`jnl`	Masked Autoencoders are Efficient Continual Federated Learners. CoRR Subarnaduti Paul, Lars-Joel Frey, Roshni Kamath, Kristian Kersting, Martin Mundt
2023	J	`jnl`	Probabilistic Circuits That Know What They Don't Know. CoRR Fabrizio Ventola, Steven Braun, Zhongjie Yu, Martin Mundt, Kristian Kersting
2023	A	`conf`	Probabilistic circuits that know what they don't know. UAI Fabrizio Ventola, Steven Braun, Zhongjie Yu, Martin Mundt, Kristian Kersting
2023	—	`ed.`	Proceedings of the 1st ContinualAI Unconference, 9 October 2023, Virtual CLAI Unconf Siddharth Swaroop, Martin Mundt, Rahaf Aljundi, Mohammad Emtiyaz Khan
2023	—	`conf`	Queer In AI: A Case Study in Community-Led Participatory AI. FAccT 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
2023	J	`jnl`	Queer In AI: A Case Study in Community-Led Participatory AI. CoRR 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
2023	J	`jnl`	Self Expanding Neural Networks. CoRR Rupert Mitchell, Martin Mundt, Kristian Kersting
2022	A*	`conf`	CLEVA-Compass: A Continual Learning Evaluation Assessment Compass to Promote Research Transparency and Comparability. ICLR Martin Mundt, Steven Lang, Quentin Delfosse, Kristian Kersting
2022	J	`jnl`	Optical see-through augmented reality can induce severe motion sickness. Displays Mara Kaufeld, Martin Mundt, Sarah Forst, Heiko Hecht
2022	A	`conf`	Predictive Whittle networks for time series. UAI Zhongjie Yu, Fabrizio Ventola, Nils Thoma, Devendra Singh Dhami, Martin Mundt, Kristian Kersting
2022	J	`jnl`	Return of the normal distribution: Flexible deep continual learning with variational auto-encoders. Neural Networks Yongwon Hong, Martin Mundt, Sungho Park, Yungjung Uh, Hyeran Byun
2022	J	`jnl`	Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition. J. Imaging Martin Mundt, Iuliia Pliushch, Sagnik Majumder, Yong Won Hong, Visvanathan Ramesh
2022	—	`conf`	When Deep Classifiers Agree: Analyzing Correlations Between Learning Order and Image Statistics. ECCV (8) Iuliia Pliushch, Martin Mundt, Nicolas Lupp, Visvanathan Ramesh
2021	—	`conf`	A Procedural World Generation Framework for Systematic Evaluation of Continual Learning. NeurIPS Datasets and Benchmarks Timm Hess, Martin Mundt, Iuliia Pliushch, Visvanathan Ramesh
2021	J	`jnl`	A Procedural World Generation Framework for Systematic Evaluation of Continual Learning. CoRR Timm Hess, Martin Mundt, Iuliia Pliushch, Visvanathan Ramesh
2021	—	`conf`	Avalanche: An End-to-End Library for Continual Learning. CVPR Workshops 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
2021	J	`jnl`	Avalanche: an End-to-End Library for Continual Learning. CoRR 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 Amhad, Adrian Popescu, Christopher Kanan, Joost van de Weijer, Tinne Tuytelaars, Davide Bacciu, Davide Maltoni
2021	J	`jnl`	CLEVA-Compass: A Continual Learning EValuation Assessment Compass to Promote Research Transparency and Comparability. CoRR Martin Mundt, Steven Lang, Quentin Delfosse, Kristian Kersting
2021	—	`—`	Designing deep neural networks for continual learning in an open world. Martin Mundt
2021	—	`conf`	Elevating Perceptual Sample Quality in PCs through Differentiable Sampling. Pre-Registration Workshop @ NeurIPS Steven Lang, Martin Mundt, Fabrizio Ventola, Robert Peharz, Kristian Kersting
2021	—	`conf`	Neural Architecture Search of Deep Priors: Towards Continual Learning Without Catastrophic Interference. CVPR Workshops Martin Mundt, Iuliia Pliushch, Visvanathan Ramesh
2021	J	`jnl`	Neural Architecture Search of Deep Priors: Towards Continual Learning without Catastrophic Interference. CoRR Martin Mundt, Iuliia Pliushch, Visvanathan Ramesh
2021	J	`jnl`	When Deep Classifiers Agree: Analyzing Correlations between Learning Order and Image Statistics. CoRR Iuliia Pliushch, Martin Mundt, Nicolas Lupp, Visvanathan Ramesh
2020	J	`jnl`	A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning. CoRR Martin Mundt, Yong Won Hong, Iuliia Pliushch, Visvanathan Ramesh
2020	Misc	`conf`	An Evaluation of Pie Menus for System Control in Virtual Reality. NordiCHI Martin Mundt, Tintu Mathew
2019	Misc	`conf`	Exploring Pie Menus for System Control Tasks in Virtual Reality. MuC Martin Mundt, Tintu Mathew
2019	A*	`conf`	Meta-Learning Convolutional Neural Architectures for Multi-Target Concrete Defect Classification With the COncrete DEfect BRidge IMage Dataset. CVPR Martin Mundt, Sagnik Majumder, Sreenivas Murali, Panagiotis Panetsos, Visvanathan Ramesh
2019	J	`jnl`	Meta-learning Convolutional Neural Architectures for Multi-target Concrete Defect Classification with the COncrete DEfect BRidge IMage Dataset. CoRR Martin Mundt, Sagnik Majumder, Sreenivas Murali, Panagiotis Panetsos, Visvanathan Ramesh
2019	—	`conf`	Open Set Recognition Through Deep Neural Network Uncertainty: Does Out-of-Distribution Detection Require Generative Classifiers? ICCV Workshops Martin Mundt, Iuliia Pliushch, Sagnik Majumder, Visvanathan Ramesh
2019	J	`jnl`	Open Set Recognition Through Deep Neural Network Uncertainty: Does Out-of-Distribution Detection Require Generative Classifiers? CoRR Martin Mundt, Iuliia Pliushch, Sagnik Majumder, Visvanathan Ramesh
2019	J	`jnl`	Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition. CoRR Martin Mundt, Sagnik Majumder, Iuliia Pliushch, Visvanathan Ramesh
2018	J	`jnl`	Rethinking Layer-wise Feature Amounts in Convolutional Neural Network Architectures. CoRR Martin Mundt, Sagnik Majumder, Tobias Weis, Visvanathan Ramesh
2017	—	`conf`	Anomaly detection for automotive visual signal transition estimation. ITSC Tobias Weis, Martin Mundt, Patrick Harding, Visvanathan Ramesh
2017	J	`jnl`	Building effective deep neural network architectures one feature at a time. CoRR Martin Mundt, Tobias Weis, Kishore Konda, Visvanathan Ramesh
2017	C	`conf`	Large-Scale Stochastic Scene Generation and Semantic Annotation for Deep Convolutional Neural Network Training in the RoboCup SPL. RoboCup Timm Hess, Martin Mundt, Tobias Weis, Visvanathan Ramesh
2017	—	`conf`	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 Helge Fischer, Matthias Heinz, Christian Leyh, Marko Ott, Sandra Döring, Cornelia Schade, Annika Löser, Martin Mundt, Anne Trojanek, Holger Rohland
2016	B	`conf`	Feature binding in deep convolution networks with recurrences, oscillations, and top-down modulated dynamics. ESANN Martin Mundt, Sebastian Blaes, Thomas Burwick