Alexander Gepperth

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 62

Top Topics

Gesture Recognition

Incremental Learning

Top Venues

Publications

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)
Stefano De Blasi, Maryam Bahrami, Elmar Engels, Alexander Gepperth
Safe contextual Bayesian optimization integrated in industrial control for self-learning machines. J. Intell. Manuf. 35 (2) (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)
Alexander Krawczyk, Alexander Gepperth
Adiabatic replay for continual learning. CoRR (2023)
Alexander Gepperth
Large-scale gradient-based training of Mixtures of Factor Analyzers. CoRR (2023)
Monika Schak, Alexander Gepperth
Free-Hand Gesture Recognition Using Conv3D-Networks with Cross Stitch Units for Multi-Modal Data. ICDL (2023)
Leander J. Féret, Alexander Gepperth, Steven Lambeck
On the improvement of model-predictive controllers. CoRR (2023)
Benedikt Bagus, Alexander Gepperth, Timothée Lesort
Beyond Supervised Continual Learning: a Review. CoRR (2022)
Monika Schak, Alexander Gepperth
Gesture MNIST: A New Free-Hand Gesture Dataset. ICANN (4) (2022)
Alexander Gepperth
Large-scale gradient-based training of Mixtures of Factor Analyzers. IJCNN (2022)
Monika Schak, Alexander Gepperth
Gesture Recognition and Multi-modal Fusion on a New Hand Gesture Dataset. ICPRAM (Revised Selected Papers) (2022)
Nadzeya Dzemidovich, Alexander Gepperth
An empirical comparison of generators in replay-based continual learning. ESANN (2022)
Benedikt Bagus, Alexander Gepperth
A Study of Continual Learning Methods for Q-Learning. CoRR (2022)
Monika Schak, Alexander Gepperth
Gesture Recognition on a New Multi-Modal Hand Gesture Dataset. ICPRAM (2022)
Alexander Gepperth, Timothée Lesort
Tutorial - Continual Learning beyond classification. ESANN (2022)
Benedikt Bagus, Alexander Gepperth
A Study of Continual Learning Methods for Q-Learning. IJCNN (2022)
Alexander Gepperth
A new perspective on probabilistic image modeling. CoRR (2022)
Alexander Gepperth
A new perspective on probabilistic image modeling. IJCNN (2022)
Alexander Gepperth, Benedikt Pfülb
Image Modeling with Deep Convolutional Gaussian Mixture Models. CoRR (2021)
Benedikt Bagus, Alexander Gepperth
An Investigation of Replay-based Approaches for Continual Learning. IJCNN (2021)
Alexander Gepperth, Benedikt Pfülb
Gradient-Based Training of Gaussian Mixture Models for High-Dimensional Streaming Data. Neural Process. Lett. 53 (6) (2021)
Benedikt Bagus, Alexander Gepperth
An Investigation of Replay-based Approaches for Continual Learning. CoRR (2021)
Benedikt Pfülb, Alexander Gepperth
Overcoming Catastrophic Forgetting with Gaussian Mixture Replay. IJCNN (2021)
Alexander Gepperth, Benedikt Pfülb
Image Modeling with Deep Convolutional Gaussian Mixture Models. IJCNN (2021)
Benedikt Pfülb, Alexander Gepperth
Overcoming Catastrophic Forgetting with Gaussian Mixture Replay. CoRR (2021)
Benedikt Pfülb, Alexander Gepperth, Benedikt Bagus
Continual Learning with Fully Probabilistic Models. CoRR (2021)
Stefano De Blasi, Alexander Neifer, Alexander Gepperth
Multi-Pronged Safe Bayesian Optimization for High Dimensions. SMC (2021)
Alexander Gepperth, Sebastian Rieger
A Survey of Machine Learning applied to Computer Networks. ESANN (2020)
Stefano De Blasi, Alexander Gepperth
SASBO: Self-Adapting Safe Bayesian Optimization. ICMLA (2020)
Monika Schak, Alexander Gepperth
On Multi-modal Fusion for Freehand Gesture Recognition. ICANN (1) (2020)
Alexander Gepperth, Benedikt Pfülb
A Rigorous Link Between Self-Organizing Maps and Gaussian Mixture Models. CoRR (2020)
Alexander Gepperth
Incremental learning with a homeostatic self-organizing neural model. Neural Comput. Appl. 32 (24) (2020)
Alexander Gepperth
An energy-based SOM model not requiring periodic boundary conditions. Neural Comput. Appl. 32 (24) (2020)
Alexander Gepperth, Benedikt Pfülb
A Rigorous Link Between Self-Organizing Maps and Gaussian Mixture Models. ICANN (2) (2020)
Christoph Hardegen, Benedikt Pfülb, Sebastian Rieger, Alexander Gepperth
Predicting Network Flow Characteristics Using Deep Learning and Real-World Network Traffic. IEEE Trans. Netw. Serv. Manag. 17 (4) (2020)
Christoph Hardegen, Benedikt Pfülb, Sebastian Rieger, Alexander Gepperth, Sven Reißmann
Flow-based Throughput Prediction using Deep Learning and Real-World Network Traffic. CNSM (2019)
Monika Schak, Alexander Gepperth
A Study on Catastrophic Forgetting in Deep LSTM Networks. ICANN (2) (2019)
Benedikt Pfülb, Alexander Gepperth
A comprehensive, application-oriented study of catastrophic forgetting in DNNs. ICLR (Poster) (2019)
Benedikt Pfülb, Alexander Gepperth, Saad Abdullah, André Kilian
Catastrophic forgetting: still a problem for DNNs. CoRR (2019)
Benedikt Pfülb, Alexander Gepperth
A comprehensive, application-oriented study of catastrophic forgetting in DNNs. CoRR (2019)
Alexander Gepperth, Florian Wiech
Simplified Computation and Interpretation of Fisher Matrices in Incremental Learning with Deep Neural Networks. ICANN (2) (2019)
Benedikt Pfülb, Christoph Hardegen, Alexander Gepperth, Sebastian Rieger
A Study of Deep Learning for Network Traffic Data Forecasting. CoRR (2019)
Benedikt Pfülb, Christoph Hardegen, Alexander Gepperth, Sebastian Rieger
A Study of Deep Learning for Network Traffic Data Forecasting. ICANN (4) (2019)
Timothée Lesort, Alexander Gepperth, Andrei Stoian, David Filliat
Marginal Replay vs Conditional Replay for Continual Learning. ICANN (2) (2019)
Monika Schak, Alexander Gepperth
Robustness of Deep LSTM Networks in Freehand Gesture Recognition. ICANN (3) (2019)
Alexander Gepperth, Benedikt Pfülb
Gradient-based training of Gaussian Mixture Models in High-Dimensional Spaces. CoRR (2019)
Timothée Lesort, Alexander Gepperth, Andrei Stoian, David Filliat
Marginal Replay vs Conditional Replay for Continual Learning. CoRR (2018)
Benedikt Pfülb, Alexander Gepperth, Saad Abdullah, André Kilian
Catastrophic Forgetting: Still a Problem for DNNs. ICANN (1) (2018)
Alexander Gepperth, Ayanava Sarkar, Thomas Kopinski
An Energy-Based Convolutional SOM Model with Self-adaptation Capabilities. ICANN (2) (2018)
Alexander Gepperth, Saad Abdullah Gondal
Incremental learning with deep neural networks using a test-time oracle. ESANN (2018)
Fabian Sachara, Finn Handmann, Nico Cremer, Thomas Kopinski, Alexander Gepperth, Uwe Handmann
A large-scale multi-pose 3D-RGB object database. IJCNN (2017)
Ayanava Sarkar, Alexander Gepperth, Uwe Handmann, Thomas Kopinski
Dynamic Hand Gesture Recognition for Mobile Systems Using Deep LSTM. IHCI (2017)
Alexander Gepperth, Cem Karaoguz
Incremental learning with self-organizing maps. WSOM (2017)
Cem Karaoguz, Alexander Gepperth
Acceleration of Prototype Based Models with Cascade Computation. ESANN (2017)
Fabian Sachara, Thomas Kopinski, Alexander Gepperth, Uwe Handmann
Free-hand gesture recognition with 3D-CNNs for in-car infotainment control in real-time. ITSC (2017)
Alexander Gepperth
An energy-based SOM model not requiring periodic boundary conditions. WSOM (2017)
Alexander Gepperth, Barbara Hammer
Incremental learning algorithms and applications. ESANN (2016)
Thomas Hecht, Alexander Gepperth
Computational Advantages of Deep Prototype-Based Learning. ICANN (2) (2016)
Thomas Hecht, Alexander Gepperth
Towards incremental deep learning: multi-level change detection in a hierarchical visual recognition architecture. ESANN (2016)
Thomas Kopinski, Fabian Sachara, Alexander Gepperth, Uwe Handmann
A Deep Learning Approach for Hand Posture Recognition from Depth Data. ICANN (2) (2016)
Alexander Gepperth, Cem Karaoguz
A Bio-Inspired Incremental Learning Architecture for Applied Perceptual Problems. Cogn. Comput. 8 (5) (2016)
Alexander Gepperth, Mathieu Lefort
Learning to be attractive: Probabilistic computation with dynamic attractor networks. ICDL-EPIROB (2016)
Thomas Hecht, Mathieu Lefort, Alexander Gepperth
Using self-organizing maps for regression: the importance of the output function. ESANN (2015)
Thomas Kopinski, Alexander Gepperth, Uwe Handmann
A Real-Time Applicable Dynamic Hand Gesture Recognition Framework. ITSC (2015)
Mathieu Lefort, Alexander Gepperth
Learning of local predictable representations in partially learnable environments. IJCNN (2015)
Thomas Hecht, Alexander Gepperth
A generative-discriminative learning model for noisy information fusion. ICDL-EPIROB (2015)
Egor Sattarov, Alexander Gepperth, Sergio A. Rodriguez F., Roger Reynaud
Calibration-free match finding between vision and LIDAR. Intelligent Vehicles Symposium (2015)
Alexander Gepperth, Thomas Hecht, Mathieu Lefort, Ursula Körner
Biologically inspired incremental learning for high-dimensional spaces. ICDL-EPIROB (2015)
Mathieu Lefort, Alexander Gepperth
Active learning of local predictable representations with artificial curiosity. ICDL-EPIROB (2015)
Alexander Gepperth, Mathieu Lefort, Thomas Hecht
Resource-efficient Incremental learning in very high dimensions. ESANN (2015)
Thomas Kopinski, Alexander Gepperth, Uwe Handmann
A simple technique for improving multi-class classification with neural networks. ESANN (2015)
Mathieu Lefort, Alexander Gepperth
PROPRE: PROjection and PREdiction for multimodal correlations learning. An application to pedestrians visual data discrimination. IJCNN (2014)
Xiao Hu, Sergio A. Rodriguez F., Alexander Gepperth
A multi-modal system for road detection and segmentation. Intelligent Vehicles Symposium (2014)
Alexander Gepperth, Mathieu Lefort
Latency-Based Probabilistic Information Processing in Recurrent Neural Hierarchies. ICANN (2014)
Mathieu Lefort, Alexander Gepperth
Discrimination of visual pedestrians data by combining projection and prediction learning. ESANN (2014)
Louis-Charles Caron, Yang Song, David Filliat, Alexander Gepperth
Neural network based 2D/3D fusion for robotic object recognition. ESANN (2014)
Alexander Gepperth
Processing and Transmission of Confidence in Recurrent Neural Hierarchies. Neural Process. Lett. 40 (1) (2014)
Alexander Gepperth, Egor Sattarov, Bernd Heisele, Sergio Alberto Rodriguez Florez
Robust visual pedestrian detection by tight coupling to tracking. ITSC (2014)
Louis-Charles Caron, David Filliat, Alexander Gepperth
Neural Network Fusion of Color, Depth and Location for Object Instance Recognition on a Mobile Robot. ECCV Workshops (3) (2014)
Thomas Hecht, Mrinal Mohit, Egor Sattarov, Alexander Gepperth
Scene context is more than a Bayesian prior: Competitive vehicle detection with restricted detectors. Intelligent Vehicles Symposium (2014)
Alexander Gepperth
Latency-based probabilistic information processing in a learning feedback hierarchy. IJCNN (2014)
Mathieu Lefort, Thomas Kopinski, Alexander Gepperth
Multimodal space representation driven by self-evaluation of predictability. ICDL-EPIROB (2014)
Thomas Kopinski, Stefan Geisler, Louis-Charles Caron, Alexander Gepperth, Uwe Handmann
A real-time applicable 3D gesture recognition system for automobile HMI. ITSC (2014)
Alexander Gepperth, Michaël Garcia Ortiz, Bernd Heisele
Real-time pedestrian detection and pose classification on a GPU. ITSC (2013)
Mathieu Dubois, Paola K. Rozo, Alexander Gepperth, Fabio A. González, David Filliat
A comparison of geometric and energy-based point cloud semantic segmentation methods. ECMR (2013)
Alexander Gepperth
Simultaneous concept formation driven by predictability. ICDL-EPIROB (2012)
David Filliat, Emmanuel Battesti, Stéphane Bazeille, Guillaume Duceux, Alexander Gepperth, Lotfi Harrath, Islem Jebari, Rafael Pereira, Adriana Tapus, Cedric Meyer, Sio-Hoi Ieng, Ryad Benosman, Eddy Cizeron, Jean-Charles Mamanna, Benoit Pothier
RGBD object recognition and visual texture classification for indoor semantic mapping. TePRA (2012)
Jens Schmüdderich, Nils Einecke, Stephan Hasler, Alexander Gepperth, Bram Bolder, Robert Kastner, Mathias Franzius, Sven Rebhan, Benjamin Dittes, Heiko Wersing, Julian Eggert, Jannik Fritsch, Christian Goerick
System approach for multi-purpose representations of traffic scene elements. ITSC (2010)
Alexander Gepperth
Object Detection and Feature Base Learning with Sparse Convolutional Neural Networks. ANNPR (2006)
Alexander Gepperth
Visual object classification by sparse convolutional neural networks. ESANN (2006)