Alexander Gepperth | DeepAI

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Featured Co-authors

David Filliat
32 publications
Timothée Lesort
23 publications
Andrei Stoian
7 publications
Benedikt Pfülb
6 publications
Benedikt Bagus
4 publications
Christoph Hardegen
1 publication
Sebastian Rieger
1 publication
Alexander Krawczyk
1 publication

∙ 08/26/2023

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

Gaussian Mixture Models (GMMs) are a standard tool in data analysis. How...

0 Alexander Gepperth, et al. ∙

∙ 03/23/2023

Adiabatic replay for continual learning

Conventional replay-based approaches to continual learning (CL) require,...

0 Alexander Krawczyk, et al. ∙

∙ 08/30/2022

Beyond Supervised Continual Learning: a Review

Continual Learning (CL, sometimes also termed incremental learning) is a...

0 Benedikt Bagus, et al. ∙

∙ 06/08/2022

A Study of Continual Learning Methods for Q-Learning

We present an empirical study on the use of continual learning (CL) meth...

0 Benedikt Bagus, et al. ∙

∙ 03/21/2022

A new perspective on probabilistic image modeling

We present the Deep Convolutional Gaussian Mixture Model (DCGMM), a new ...

0 Alexander Gepperth, et al. ∙

∙ 08/15/2021

An Investigation of Replay-based Approaches for Continual Learning

Continual learning (CL) is a major challenge of machine learning (ML) an...

0 Benedikt Bagus, et al. ∙

∙ 04/19/2021

Continual Learning with Fully Probabilistic Models

We present an approach for continual learning (CL) that is based on full...

0 Benedikt Pfülb, et al. ∙

∙ 04/19/2021

Overcoming Catastrophic Forgetting with Gaussian Mixture Replay

We present Gaussian Mixture Replay (GMR), a rehearsal-based approach for...

18 Benedikt Pfülb, et al. ∙

∙ 09/24/2020

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

This work presents a mathematical treatment of the relation between Self...

0 Alexander Gepperth, et al. ∙

∙ 12/18/2019

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

We present an approach for efficiently training Gaussian Mixture Models ...

55 Alexander Gepperth, et al. ∙

∙ 09/10/2019

A Study of Deep Learning for Network Traffic Data Forecasting

We present a study of deep learning applied to the domain of network tra...

0 Benedikt Pfülb, et al. ∙

∙ 10/29/2018

Marginal Replay vs Conditional Replay for Continual Learning

We present a new replay-based method of continual classification learnin...

0 Timothée Lesort, et al. ∙

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