| 2025 | ESANN | Don't drift away: Advances and Applications of Streaming and Continual Learning. | Andrea Cossu, Davide Bacciu, Alessio Bernardo, Emanuele Della Valle, Alexander Gepperth, Federico Giannini, Barbara Hammer, Giacomo Ziffer |
| 2025 | ESANN | Reward Incremental Learning. | Yannick Denker, Alexander Gepperth |
| 2025 | ESANN | Continual Unlearning through Memory Suppression. | Alexander Krawczyk, Alexander Gepperth |
| 2024 | CVPR | An analysis of best-practice strategies for replay and rehearsal in continual learning. | Alexander Krawczyk, Alexander Gepperth |
| 2024 | ESANN | Continual Learning of Deep Neural Networks in The Age of Big Data. | Alexander Gepperth, Timothe Lesort |
| 2024 | IJCNN | Adiabatic replay for continual learning. | Alexander Krawczyk, Alexander Gepperth |
| 2022 | ESANN | An empirical comparison of generators in replay-based continual learning. | Nadzeya Dzemidovich, Alexander Gepperth |
| 2022 | ESANN | Tutorial - Continual Learning beyond classification. | Alexander Gepperth, Timothe Lesort |
| 2022 | ICANN | Gesture MNIST: A New Free-Hand Gesture Dataset. | Monika Schak, Alexander Gepperth |
| 2022 | IJCNN | A Study of Continual Learning Methods for Q-Learning. | Benedikt Bagus, Alexander Gepperth |
| 2022 | IJCNN | A new perspective on probabilistic image modeling. | Alexander Gepperth |
| 2022 | IJCNN | Large-scale gradient-based training of Mixtures of Factor Analyzers. | Alexander Gepperth |
| 2022 | ICPRAM | Gesture Recognition on a New Multi-Modal Hand Gesture Dataset. | Monika Schak, Alexander Gepperth |
| 2022 | ICPRAM | Gesture Recognition and Multi-modal Fusion on a New Hand Gesture Dataset. | Monika Schak, Alexander Gepperth |
| 2021 | IJCNN | An Investigation of Replay-based Approaches for Continual Learning. | Benedikt Bagus, Alexander Gepperth |
| 2021 | IJCNN | Image Modeling with Deep Convolutional Gaussian Mixture Models. | Alexander Gepperth, Benedikt Pflb |
| 2021 | IJCNN | Overcoming Catastrophic Forgetting with Gaussian Mixture Replay. | Benedikt Pflb, Alexander Gepperth |
| 2021 | SMC | Multi-Pronged Safe Bayesian Optimization for High Dimensions. | Stefano De Blasi, Alexander Neifer, Alexander Gepperth |
| 2020 | ESANN | A Survey of Machine Learning applied to Computer Networks. | Alexander Gepperth, Sebastian Rieger |
| 2020 | ICANN | A Rigorous Link Between Self-Organizing Maps and Gaussian Mixture Models. | Alexander Gepperth, Benedikt Pflb |
| 2020 | ICANN | On Multi-modal Fusion for Freehand Gesture Recognition. | Monika Schak, Alexander Gepperth |
| 2020 | ICMLA | SASBO: Self-Adapting Safe Bayesian Optimization. | Stefano De Blasi, Alexander Gepperth |
| 2019 | CNSM | Flow-based Throughput Prediction using Deep Learning and Real-World Network Traffic. | Christoph Hardegen, Benedikt Pflb, Sebastian Rieger, Alexander Gepperth, Sven Reimann |
| 2019 | ICANN | Simplified Computation and Interpretation of Fisher Matrices in Incremental Learning with Deep Neural Networks. | Alexander Gepperth, Florian Wiech |
| 2019 | ICANN | Marginal Replay vs Conditional Replay for Continual Learning. | Timothe Lesort, Alexander Gepperth, Andrei Stoian, David Filliat |
| 2019 | ICANN | A Study of Deep Learning for Network Traffic Data Forecasting. | Benedikt Pflb, Christoph Hardegen, Alexander Gepperth, Sebastian Rieger |
| 2019 | ICANN | A Study on Catastrophic Forgetting in Deep LSTM Networks. | Monika Schak, Alexander Gepperth |
| 2019 | ICANN | Robustness of Deep LSTM Networks in Freehand Gesture Recognition. | Monika Schak, Alexander Gepperth |
| 2019 | ICLR | A comprehensive, application-oriented study of catastrophic forgetting in DNNs. | Benedikt Pflb, Alexander Gepperth |
| 2018 | ESANN | Incremental learning with deep neural networks using a test-time oracle. | Alexander Gepperth, Saad Abdullah Gondal |
| 2018 | ICANN | An Energy-Based Convolutional SOM Model with Self-adaptation Capabilities. | Alexander Gepperth, Ayanava Sarkar, Thomas Kopinski |
| 2018 | ICANN | Catastrophic Forgetting: Still a Problem for DNNs. | Benedikt Pflb, Alexander Gepperth, Saad Abdullah, Andr Kilian |
| 2017 | ESANN | Acceleration of Prototype Based Models with Cascade Computation. | Cem Karaoguz, Alexander Gepperth |
| 2017 | IJCNN | A large-scale multi-pose 3D-RGB object database. | Fabian Sachara, Finn Handmann, Nico Cremer, Thomas Kopinski, Alexander Gepperth, Uwe Handmann |
| 2016 | ESANN | Incremental learning algorithms and applications. | Alexander Gepperth, Barbara Hammer |
| 2016 | ESANN | Towards incremental deep learning: multi-level change detection in a hierarchical visual recognition architecture. | Thomas Hecht, Alexander Gepperth |
| 2016 | ICANN | Computational Advantages of Deep Prototype-Based Learning. | Thomas Hecht, Alexander Gepperth |
| 2016 | ICANN | A Deep Learning Approach for Hand Posture Recognition from Depth Data. | Thomas Kopinski, Fabian Sachara, Alexander Gepperth, Uwe Handmann |
| 2015 | ESANN | Resource-efficient Incremental learning in very high dimensions. | Alexander Gepperth, Mathieu Lefort, Thomas Hecht |
| 2015 | ESANN | Using self-organizing maps for regression: the importance of the output function. | Thomas Hecht, Mathieu Lefort, Alexander Gepperth |
| 2015 | ESANN | A simple technique for improving multi-class classification with neural networks. | Thomas Kopinski, Alexander Gepperth, Uwe Handmann |
| 2015 | IJCNN | Learning of local predictable representations in partially learnable environments. | Mathieu Lefort, Alexander Gepperth |
| 2014 | ECCV | Neural Network Fusion of Color, Depth and Location for Object Instance Recognition on a Mobile Robot. | Louis-Charles Caron, David Filliat, Alexander Gepperth |
| 2014 | ESANN | Neural network based 2D/3D fusion for robotic object recognition. | Louis-Charles Caron, Yang Song, David Filliat, Alexander Gepperth |
| 2014 | ESANN | Discrimination of visual pedestrians data by combining projection and prediction learning. | Mathieu Lefort, Alexander Gepperth |
| 2014 | ICANN | Latency-Based Probabilistic Information Processing in Recurrent Neural Hierarchies. | Alexander Gepperth, Mathieu Lefort |
| 2014 | IJCNN | Latency-based probabilistic information processing in a learning feedback hierarchy. | Alexander Gepperth |
| 2014 | IJCNN | PROPRE: PROjection and PREdiction for multimodal correlations learning. An application to pedestrians visual data discrimination. | Mathieu Lefort, Alexander Gepperth |
| 2006 | ESANN | Visual object classification by sparse convolutional neural networks. | Alexander Gepperth |