Alexander Gepperth

According to our database, Alexander Gepperth authored at least 104 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Safe contextual Bayesian optimization integrated in industrial control for self-learning machines.

Stefano De Blasi, Maryam Bahrami, Elmar Engels, Alexander Gepperth

J. Intell. Manuf., February, 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

Trans. Mach. Learn. Res., 2024

Continual Reinforcement Learning Without Replay Buffers.

Alexander Krawczyk, Benedikt Bagus, Yannick Denker, Alexander Gepperth

Proceedings of the 12th IEEE International Conference on Intelligent Systems, 2024

Enhancing the Robustness of Model-Predictive Control using GMMs as Outlier Detection.

Leander J. Féret, Alexander Gepperth, Steven Lambeck

Proceedings of the 12th IEEE International Conference on Intelligent Systems, 2024

Adiabatic replay for continual learning.

Alexander Krawczyk, Alexander Gepperth

Proceedings of the International Joint Conference on Neural Networks, 2024

An analysis of best-practice strategies for replay and rehearsal in continual learning.

Alexander Krawczyk, Alexander Gepperth

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

On the improvement of model-predictive controllers.

Leander J. Féret, Alexander Gepperth, Steven Lambeck

CoRR, 2023

Free-Hand Gesture Recognition Using Conv3D-Networks with Cross Stitch Units for Multi-Modal Data.

Monika Schak, Alexander Gepperth

Proceedings of the IEEE International Conference on Development and Learning, 2023

2022

Beyond Supervised Continual Learning: a Review.

Benedikt Bagus, Alexander Gepperth, Timothée Lesort

CoRR, 2022

Large-scale gradient-based training of Mixtures of Factor Analyzers.

Alexander Gepperth

Proceedings of the International Joint Conference on Neural Networks, 2022

A new perspective on probabilistic image modeling.

Alexander Gepperth

Proceedings of the International Joint Conference on Neural Networks, 2022

A Study of Continual Learning Methods for Q-Learning.

Benedikt Bagus, Alexander Gepperth

Proceedings of the International Joint Conference on Neural Networks, 2022

Gesture Recognition and Multi-modal Fusion on a New Hand Gesture Dataset.

Monika Schak, Alexander Gepperth

Proceedings of the Pattern Recognition Applications and Methods, 2022

Gesture Recognition on a New Multi-Modal Hand Gesture Dataset.

Monika Schak, Alexander Gepperth

Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods, 2022

Gesture MNIST: A New Free-Hand Gesture Dataset.

Monika Schak, Alexander Gepperth

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022

Tutorial - Continual Learning beyond classification.

Alexander Gepperth, Timothée Lesort

Proceedings of the 30th European Symposium on Artificial Neural Networks, 2022

An empirical comparison of generators in replay-based continual learning.

Nadzeya Dzemidovich, Alexander Gepperth

Proceedings of the 30th European Symposium on Artificial Neural Networks, 2022

2021

Gradient-Based Training of Gaussian Mixture Models for High-Dimensional Streaming Data.

Alexander Gepperth, Benedikt Pfülb

Neural Process. Lett., 2021

Continual Learning with Fully Probabilistic Models.

Benedikt Pfülb, Alexander Gepperth, Benedikt Bagus

CoRR, 2021

Multi-Pronged Safe Bayesian Optimization for High Dimensions.

Stefano De Blasi, Alexander Neifer, Alexander Gepperth

Proceedings of the 2021 IEEE International Conference on Systems, Man, and Cybernetics, 2021

Overcoming Catastrophic Forgetting with Gaussian Mixture Replay.

Benedikt Pfülb, Alexander Gepperth

Proceedings of the International Joint Conference on Neural Networks, 2021

Image Modeling with Deep Convolutional Gaussian Mixture Models.

Alexander Gepperth, Benedikt Pfülb

Proceedings of the International Joint Conference on Neural Networks, 2021

An Investigation of Replay-based Approaches for Continual Learning.

Benedikt Bagus, Alexander Gepperth

Proceedings of the International Joint Conference on Neural Networks, 2021

2020

Predicting Network Flow Characteristics Using Deep Learning and Real-World Network Traffic.

Christoph Hardegen, Benedikt Pfülb, Sebastian Rieger, Alexander Gepperth

IEEE Trans. Netw. Serv. Manag., 2020

Incremental learning with a homeostatic self-organizing neural model.

Alexander Gepperth

Neural Comput. Appl., 2020

An energy-based SOM model not requiring periodic boundary conditions.

Alexander Gepperth

Neural Comput. Appl., 2020

SASBO: Self-Adapting Safe Bayesian Optimization.

Stefano De Blasi, Alexander Gepperth

Proceedings of the 19th IEEE International Conference on Machine Learning and Applications, 2020

On Multi-modal Fusion for Freehand Gesture Recognition.

Monika Schak, Alexander Gepperth

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2020, 2020

A Rigorous Link Between Self-Organizing Maps and Gaussian Mixture Models.

Alexander Gepperth, Benedikt Pfülb

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2020, 2020

A Survey of Machine Learning applied to Computer Networks.

Alexander Gepperth, Sebastian Rieger

Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

2019

Gradient-based training of Gaussian Mixture Models in High-Dimensional Spaces.

Alexander Gepperth, Benedikt Pfülb

CoRR, 2019

A comprehensive, application-oriented study of catastrophic forgetting in DNNs.

Benedikt Pfülb, Alexander Gepperth

Proceedings of the 7th International Conference on Learning Representations, 2019

Robustness of Deep LSTM Networks in Freehand Gesture Recognition.

Monika Schak, Alexander Gepperth

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Image Processing, 2019

A Study on Catastrophic Forgetting in Deep LSTM Networks.

Monika Schak, Alexander Gepperth

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Deep Learning, 2019

A Study of Deep Learning for Network Traffic Data Forecasting.

Benedikt Pfülb, Christoph Hardegen, Alexander Gepperth, Sebastian Rieger

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Text and Time Series, 2019

Marginal Replay vs Conditional Replay for Continual Learning.

Timothée Lesort, Alexander Gepperth, Andrei Stoian, David Filliat

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Deep Learning, 2019

Simplified Computation and Interpretation of Fisher Matrices in Incremental Learning with Deep Neural Networks.

Alexander Gepperth, Florian Wiech

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Deep Learning, 2019

Flow-based Throughput Prediction using Deep Learning and Real-World Network Traffic.

Christoph Hardegen, Benedikt Pfülb, Sebastian Rieger, Alexander Gepperth, Sven Reißmann

Proceedings of the 15th International Conference on Network and Service Management, 2019

2018

Catastrophic Forgetting: Still a Problem for DNNs.

Benedikt Pfülb, Alexander Gepperth, Saad Abdullah, André Kilian

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

An Energy-Based Convolutional SOM Model with Self-adaptation Capabilities.

Alexander Gepperth, Ayanava Sarkar, Thomas Kopinski

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

Incremental learning with deep neural networks using a test-time oracle.

Alexander Gepperth, Saad Abdullah Gondal

Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

2017

Incremental learning with self-organizing maps.

Alexander Gepperth, Cem Karaoguz

Proceedings of the 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, 2017

Free-hand gesture recognition with 3D-CNNs for in-car infotainment control in real-time.

Fabian Sachara, Thomas Kopinski, Alexander Gepperth, Uwe Handmann

Proceedings of the 20th IEEE International Conference on Intelligent Transportation Systems, 2017

A large-scale multi-pose 3D-RGB object database.

Fabian Sachara, Finn Handmann, Nico Cremer, Thomas Kopinski, Alexander Gepperth, Uwe Handmann

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Dynamic Hand Gesture Recognition for Mobile Systems Using Deep LSTM.

Ayanava Sarkar, Alexander Gepperth, Uwe Handmann, Thomas Kopinski

Proceedings of the Intelligent Human Computer Interaction - 9th International Conference, 2017

Acceleration of Prototype Based Models with Cascade Computation.

Cem Karaoguz, Alexander Gepperth

Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

2016

Dynamic attention priors: a new and efficient concept for improving object detection.

Alexander Rainer Tassilo Gepperth, Michaël Garcia Ortiz, Egor Sattarov, Bernd Heisele

Neurocomputing, 2016

A Bio-Inspired Incremental Learning Architecture for Applied Perceptual Problems.

Alexander Gepperth, Cem Karaoguz

Cogn. Comput., 2016

A Generative Learning Approach to Sensor Fusion and Change Detection.

Alexander R. T. Gepperth, Thomas Hecht, Mandar Gogate

Cogn. Comput., 2016

Incremental learning for bootstrapping object classifier models.

Cem Karaoguz, Alexander R. T. Gepperth

Proceedings of the 19th IEEE International Conference on Intelligent Transportation Systems, 2016

Learning to be attractive: Probabilistic computation with dynamic attractor networks.

Alexander Gepperth, Mathieu Lefort

Proceedings of the 2016 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics, 2016

A time-of-flight-based hand posture database for human-machine interaction.

Thomas Kopinski, Alexander R. T. Gepperth, Uwe Handmann

Proceedings of the 14th International Conference on Control, 2016

A Deep Learning Approach for Hand Posture Recognition from Depth Data.

Thomas Kopinski, Fabian Sachara, Alexander Gepperth, Uwe Handmann

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2016, 2016

Computational Advantages of Deep Prototype-Based Learning.

Thomas Hecht, Alexander Gepperth

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2016, 2016

Towards incremental deep learning: multi-level change detection in a hierarchical visual recognition architecture.

Thomas Hecht, Alexander Gepperth

Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

Incremental learning algorithms and applications.

Alexander Gepperth, Barbara Hammer

Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

New learning paradigms for real-world environment perception.

Alexander R. T. Gepperth

, 2016

2015

Calibration-free match finding between vision and LIDAR.

Egor Sattarov, Alexander Gepperth, Sergio Alberto Rodriguez F., Roger Reynaud

Proceedings of the 2015 IEEE Intelligent Vehicles Symposium, 2015

A light-weight real-time applicable hand gesture recognition system for automotive applications.

Thomas Kopinski, Stephane Magand, Alexander Rainer Tassilo Gepperth, Uwe Handmann

Proceedings of the 2015 IEEE Intelligent Vehicles Symposium, 2015

A Real-Time Applicable Dynamic Hand Gesture Recognition Framework.

Thomas Kopinski, Alexander Gepperth, Uwe Handmann

Proceedings of the IEEE 18th International Conference on Intelligent Transportation Systems, 2015

Learning of local predictable representations in partially learnable environments.

Mathieu Lefort, Alexander Gepperth

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

A pragmatic approach to multi-class classification.

Thomas Kopinski, Stephane Magand, Uwe Handmann, Alexander Rainer Tassilo Gepperth

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Active learning of local predictable representations with artificial curiosity.

Mathieu Lefort, Alexander Gepperth

Proceedings of the 2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics, 2015

A generative-discriminative learning model for noisy information fusion.

Thomas Hecht, Alexander Gepperth

Proceedings of the 2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics, 2015

Biologically inspired incremental learning for high-dimensional spaces.

Alexander Gepperth, Thomas Hecht, Mathieu Lefort, Ursula Körner

Proceedings of the 2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics, 2015

A simple technique for improving multi-class classification with neural networks.

Thomas Kopinski, Alexander Gepperth, Uwe Handmann

Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

Using self-organizing maps for regression: the importance of the output function.

Thomas Hecht, Mathieu Lefort, Alexander Gepperth

Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

Resource-efficient Incremental learning in very high dimensions.

Alexander Gepperth, Mathieu Lefort, Thomas Hecht

Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

2014

Processing and Transmission of Confidence in Recurrent Neural Hierarchies.

Alexander Gepperth

Neural Process. Lett., 2014

A multi-modal system for road detection and segmentation.

Xiao Hu, Sergio Alberto Rodriguez F., Alexander Gepperth

Proceedings of the 2014 IEEE Intelligent Vehicles Symposium Proceedings, 2014

Scene context is more than a Bayesian prior: Competitive vehicle detection with restricted detectors.

Thomas Hecht, Mrinal Mohit, Egor Sattarov, Alexander Gepperth

Proceedings of the 2014 IEEE Intelligent Vehicles Symposium Proceedings, 2014

Context-based vector fields for multi-object tracking in application to road traffic.

Egor Sattarov, Sergio Alberto Rodriguez F., Alexander R. T. Gepperth, Roger Reynaud

Proceedings of the 17th International IEEE Conference on Intelligent Transportation Systems, 2014

A real-time applicable 3D gesture recognition system for automobile HMI.

Thomas Kopinski, Stefan Geisler, Louis-Charles Caron, Alexander Gepperth, Uwe Handmann

Proceedings of the 17th International IEEE Conference on Intelligent Transportation Systems, 2014

Robust visual pedestrian detection by tight coupling to tracking.

Alexander Gepperth, Egor Sattarov, Bernd Heisele, Sergio Alberto Rodriguez Florez

Proceedings of the 17th International IEEE Conference on Intelligent Transportation Systems, 2014

PROPRE: PROjection and PREdiction for multimodal correlations learning. An application to pedestrians visual data discrimination.

Mathieu Lefort, Alexander Gepperth

Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Latency-based probabilistic information processing in a learning feedback hierarchy.

Alexander Gepperth

Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Multimodal space representation driven by self-evaluation of predictability.

Mathieu Lefort, Thomas Kopinski, Alexander Gepperth

Proceedings of the 4th International Conference on Development and Learning and on Epigenetic Robotics, 2014

Neural Network Based Data Fusion for Hand Pose Recognition with Multiple ToF Sensors.

Thomas Kopinski, Alexander Rainer Tassilo Gepperth, Stefan Geisler, Uwe Handmann

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2014, 2014

Latency-Based Probabilistic Information Processing in Recurrent Neural Hierarchies.

Alexander Gepperth, Mathieu Lefort

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2014, 2014

Discrimination of visual pedestrians data by combining projection and prediction learning.

Mathieu Lefort, Alexander Gepperth

Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Neural network based 2D/3D fusion for robotic object recognition.

Louis-Charles Caron, Yang Song, David Filliat, Alexander Gepperth

Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Neural Network Fusion of Color, Depth and Location for Object Instance Recognition on a Mobile Robot.

Louis-Charles Caron, David Filliat, Alexander Gepperth

Proceedings of the Computer Vision - ECCV 2014 Workshops, 2014

2013

Real-time pedestrian detection and pose classification on a GPU.

Alexander Gepperth, Michaël Garcia Ortiz, Bernd Heisele

Proceedings of the 16th International IEEE Conference on Intelligent Transportation Systems, 2013

A comparison of geometric and energy-based point cloud semantic segmentation methods.

Mathieu Dubois, Paola K. Rozo, Alexander Gepperth, Fabio A. González, David Filliat

Proceedings of the 2013 European Conference on Mobile Robots, 2013

2012

The contribution of context information: A case study of object recognition in an intelligent car.

Alexander Rainer Tassilo Gepperth, Benjamin Dittes, Michaël Garcia Ortiz

Neurocomputing, 2012

RGBD object recognition and visual texture classification for indoor semantic mapping.

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

Proceedings of the 2012 IEEE International Conference on Technologies for Practical Robot Applications, 2012

Co-training of context models for real-time vehicle detection.

Alexander Rainer Tassilo Gepperth

Proceedings of the 2012 IEEE Intelligent Vehicles Symposium, 2012

Simultaneous concept formation driven by predictability.

Alexander Gepperth

Proceedings of the 2012 IEEE International Conference on Development and Learning and Epigenetic Robotics, 2012

2011

Biased Competition in Visual Processing Hierarchies: A Learning Approach Using Multiple Cues.

Alexander Rainer Tassilo Gepperth, Sven Rebhan, Stephan Hasler, Jannik Fritsch

Cogn. Comput., 2011

Behavior prediction at multiple time-scales in inner-city scenarios.

Michaël Garcia Ortiz, Jannik Fritsch, Franz Kummert, Alexander Rainer Tassilo Gepperth

Proceedings of the IEEE Intelligent Vehicles Symposium (IV), 2011

Situation-specific learning for ego-vehicle behavior prediction systems.

Michaël Garcia Ortiz, Jens Schmüdderich, Franz Kummert, Alexander R. T. Gepperth

Proceedings of the 14th International IEEE Conference on Intelligent Transportation Systems, 2011

2010

System approach for multi-purpose representations of traffic scene elements.

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

Proceedings of the 13th International IEEE Conference on Intelligent Transportation Systems, 2010

Autonomous Generation of Internal Representations for Associative Learning.

Michaël Garcia Ortiz, Benjamin Dittes, Jannik Fritsch, Alexander Rainer Tassilo Gepperth

Proceedings of the Artificial Neural Networks - ICANN 2010, 2010

2009

A Hierarchical System Integration Approach with Application to Visual Scene Exploration for Driver Assistance.

Benjamin Dittes, Martin Heracles, Thomas Michalke, Robert Kastner, Alexander Rainer Tassilo Gepperth, Jannik Fritsch, Christian Goerick

Proceedings of the Computer Vision Systems, 2009

Self-management for neural dynamics in brain-like information processing.

Benjamin Dittes, Alexander Rainer Tassilo Gepperth, Antonello Ceravola, Jannik Fritsch, Christian Goerick

Proceedings of the 6th International Conference on Autonomic Computing, 2009

2008

Automatic detection of exonic splicing enhancers (ESEs) using SVMs.

Britta Mersch, Alexander Rainer Tassilo Gepperth, Sándor Suhai, Agnes Hotz-Wagenblatt

BMC Bioinform., 2008

An Attention-based System Approach for Scene Analysis in Driver Assistance (Ein aufmerksamkeitsbasierter Systemansatz zur Szenenanalyse in der Fahrerassistenz).

Thomas Michalke, Robert Kastner, Jürgen Adamy, Sven Bone, Falko Waibel, Marcus Kleinehagenbrock, Jens Gayko, Alexander Rainer Tassilo Gepperth, Jannik Fritsch, Christian Goerick

Autom., 2008

Computationally Efficient Neural Field Dynamics.

Alexander Rainer Tassilo Gepperth, Jannik Fritsch, Christian Goerick

Proceedings of the 16th European Symposium on Artificial Neural Networks, 2008

2007

Color Object Recognition in Real-World Scenes.

Alexander Rainer Tassilo Gepperth, Britta Mersch, Jannik Fritsch, Christian Goerick

Proceedings of the Artificial Neural Networks, 2007

2006

Multi-Objective Neural Network Optimization for Visual Object Detection.

Stefan Roth, Alexander Rainer Tassilo Gepperth, Christian Igel

Proceedings of the Multi-Objective Machine Learning, 2006

Neural learning methods for visual object detection.

Alexander Rainer Tassilo Gepperth

PhD thesis, 2006

Applications of multi-objective structure optimization.

Alexander Rainer Tassilo Gepperth, Stefan Roth

Neurocomputing, 2006

Visual object classification by sparse convolutional neural networks.

Alexander Gepperth

Proceedings of the 14th European Symposium on Artificial Neural Networks, 2006

Object Detection and Feature Base Learning with Sparse Convolutional Neural Networks.

Alexander Gepperth

Proceedings of the Artificial Neural Networks in Pattern Recognition, Second IAPR Workshop, 2006