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Mats L. Richter
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Books and Theses
- 2022
- [b1]Mats L. Richter:
Towards efficient convolutional neural architecture design: exploring the properties of neural architectures using spectral decomposition and logistic regression probes. University of Osnabrück, Germany, 2022, pp. 1-196
Journal Articles
- 2024
- [j2]Adam Ibrahim, Benjamin Thérien, Kshitij Gupta, Mats L. Richter, Quentin Gregory Anthony, Eugene Belilovsky, Timothée Lesort, Irina Rish:
Simple and Scalable Strategies to Continually Pre-train Large Language Models. Trans. Mach. Learn. Res. 2024 (2024) - 2022
- [j1]Justin Shenk
, Mats L. Richter, Wolf Byttner:
Delve: Neural Network Feature Variance Analysis. J. Open Source Softw. 7(69): 3992 (2022)
Conference and Workshop Papers
- 2025
- [c9]Pablo Pernias, Dominic Rampas, Mats L. Richter, Christopher J. Pal, Marc Aubreville:
Abstract: Würstchen - An Efficient Architecture for Large-scale Text-to-image Diffusion Models. Bildverarbeitung für die Medizin 2025: 269 - 2024
- [c8]Pablo Pernias, Dominic Rampas, Mats L. Richter, Christopher Pal, Marc Aubreville:
Würstchen: An Efficient Architecture for Large-Scale Text-to-Image Diffusion Models. ICLR 2024 - 2023
- [c7]Leila Malihi, Ursula Hübner, Mats L. Richter, Maurice Moelleken, Mareike Przysucha, Dorothee Busch, Jan Heggemann, Guido Hafer, Stefan Wiemeyer, Gunther Heidemann, Joachim Dissemond, Cornelia Erfurt-Berge, Carlotta B. C. Barkhau, Achim Hendriks, Jens Hüsers
Can Synthetic Images Improve CNN Performance in Wound Image Classification? MIE 2023: 927-931 - 2022
- [c6]Leila Malihi, Jens Hüsers, Mats L. Richter, Maurice Moelleken, Mareike Przysucha, Dorothee Busch, Jan Heggemann, Guido Hafer, Stefan Wiemeyer, Gunther Heidemann, Joachim Dissemond, Cornelia Erfurt-Berge, Ursula Hübner:
Automatic Wound Type Classification with Convolutional Neural Networks. ICIMTH 2022: 281-284 - [c5]Jens Hüsers, Maurice Moelleken, Mats L. Richter, Mareike Przysucha, Leila Malihi, Dorothee Busch, Nina-Alexandra Götz, Jan Heggemann, Guido Hafer, Stefan Wiemeyer, Birgit Babitsch, Gunther Heidemann, Joachim Dissemond, Cornelia Erfurt-Berge, Ursula Hübner:
An Image Based Object Recognition System for Wound Detection and Classification of Diabetic Foot and Venous Leg Ulcers. MIE 2022: 63-67 - 2021
- [c4]Mats L. Richter, Justin Shenk, Wolf Byttner, Anna Wiedenroth, Mikael Huss:
Feature Space Saturation during Training. BMVC 2021: 17 - [c3]Julius Schöning
AI-Based Crop Rotation for Sustainable Agriculture Worldwide. GHTC 2021: 142-146 - [c2]Mats L. Richter, Wolf Byttner, Ulf Krumnack, Anna Wiedenroth
(Input) Size Matters for CNN Classifiers. ICANN (2) 2021: 133-144 - [c1]Mats L. Richter, Julius Schöning
Should You Go Deeper? Optimizing Convolutional Neural Network Architectures without Training. ICMLA 2021: 964-971
Informal and Other Publications
- 2025
- [i10]Mathieu Andreux, Breno Baldas Skuk, Hamza Benchekroun, Emilien Biré, Antoine Bonnet, Riaz Bordie, Nathan Bout, Matthias Brunel, Pierre-Louis Cedoz, Antoine Chassang, Mickaël Chen, Alexandra D. Constantinou, Antoine d'Andigné, Hubert de La Jonquière, Aurélien Delfosse, Ludovic Denoyer, Alexis Deprez, Augustin Derupti, Michael Eickenberg, Mathïs Federico, Charles Kantor, Xavier Koegler, Yann Labbé, Matthew C. H. Lee, Erwan Le Jumeau de Kergaradec, Amir Mahla, Avshalom Manevich, Adrien Maret, Charles Masson, Rafaël Maurin, Arturo Mena, Philippe Modard, Axel Moyal, Axel Nguyen Kerbel, Julien Revelle, Mats L. Richter, María Santos, Laurent Sifre, Maxime Theillard, Marc Thibault, Louis Thiry, Léo Tronchon, Nicolas Usunier, Tony Wu:
Surfer-H Meets Holo1: Cost-Efficient Web Agent Powered by Open Weights. CoRR abs/2506.02865 (2025) - 2024
- [i9]Adam Ibrahim, Benjamin Thérien, Kshitij Gupta, Mats L. Richter, Quentin Anthony, Timothée Lesort, Eugene Belilovsky, Irina Rish:
Simple and Scalable Strategies to Continually Pre-train Large Language Models. CoRR abs/2403.08763 (2024) - [i8]Matthew Fortier, Mats L. Richter, Oliver Sonnentag, Chris Pal:
CarbonSense: A Multimodal Dataset and Baseline for Carbon Flux Modelling. CoRR abs/2406.04940 (2024) - 2023
- [i7]Kshitij Gupta, Benjamin Thérien, Adam Ibrahim, Mats L. Richter, Quentin Anthony, Eugene Belilovsky, Irina Rish, Timothée Lesort:
Continual Pre-Training of Large Language Models: How to (re)warm your model? CoRR abs/2308.04014 (2023) - 2022
- [i6]Mats L. Richter, Christopher Pal:
Receptive Field Refinement for Convolutional Neural Networks Reliably Improves Predictive Performance. CoRR abs/2211.14487 (2022) - 2021
- [i5]Mats L. Richter, Wolf Byttner, Ulf Krumnack, Ludwig Schallner, Justin Shenk:
Size Matters. CoRR abs/2102.01582 (2021) - [i4]Mats L. Richter, Leila Malihi, Anne-Kathrin Patricia Windler, Ulf Krumnack:
Exploring the Properties and Evolution of Neural Network Eigenspaces during Training. CoRR abs/2106.09526 (2021) - [i3]Mats L. Richter, Julius Schöning
Should You Go Deeper? Optimizing Convolutional Neural Network Architectures without Training by Receptive Field Analysis. CoRR abs/2106.12307 (2021) - 2020
- [i2]Justin Shenk, Mats L. Richter, Wolf Byttner, Anders Arpteg, Mikael Huss:
Feature Space Saturation during Training. CoRR abs/2006.08679 (2020) - 2019
- [i1]Justin Shenk, Mats L. Richter, Anders Arpteg, Mikael Huss:
Spectral Analysis of Latent Representations. CoRR abs/1907.08589 (2019)
Coauthor Index
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