Spectral Analysis of Latent Representations. - Justin Shenk; Mats L. Richter; Anders Arpteg; Mikael Huss (CoRR, 2019)

Feature Space Saturation during Training. - Justin Shenk; Mats L. Richter; Wolf Byttner; Anders Arpteg; Mikael Huss (CoRR, 2020)

Feature Space Saturation during Training. - Mats L. Richter; Justin Shenk; Wolf Byttner; Anna Wiedenroth; Mikael Huss (BMVC, 2021)

AI-Based Crop Rotation for Sustainable Agriculture Worldwide. - Julius Schöning; Mats L. Richter (GHTC, 2021)

(Input) Size Matters for CNN Classifiers. - Mats L. Richter; Wolf Byttner; Ulf Krumnack; Anna Wiedenroth; Ludwig Schallner; Justin Shenk (ICANN (2), 2021)

Should You Go Deeper? Optimizing Convolutional Neural Network Architectures without Training. - Mats L. Richter; Julius Schöning; Anna Wiedenroth; Ulf Krumnack (ICMLA, 2021)

Size Matters. - Mats L. Richter; Wolf Byttner; Ulf Krumnack; Ludwig Schallner; Justin Shenk (CoRR, 2021)

Exploring the Properties and Evolution of Neural Network Eigenspaces during Training. - Mats L. Richter; Leila Malihi; Anne-Kathrin Patricia Windler; Ulf Krumnack (CoRR, 2021)

Should You Go Deeper? Optimizing Convolutional Neural Network Architectures without Training by Receptive Field Analysis. - Mats L. Richter; Julius Schöning; Ulf Krumnack (CoRR, 2021)

Automatic Wound Type Classification with Convolutional Neural Networks. - 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; et al. (ICIMTH, 2022)

An Image Based Object Recognition System for Wound Detection and Classification of Diabetic Foot and Venous Leg Ulcers. - 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; et al. (MIE, 2022)

Receptive Field Refinement for Convolutional Neural Networks Reliably Improves Predictive Performance. - Mats L. Richter; Christopher Pal (CoRR, 2022)

Delve: Neural Network Feature Variance Analysis. - Justin Shenk; Mats L. Richter; Wolf Byttner (J. Open Source Softw., 2022)

Towards efficient convolutional neural architecture design: exploring the properties of neural architectures using spectral decomposition and logistic regression probes. - Mats L. Richter (2022)

Can Synthetic Images Improve CNN Performance in Wound Image Classification? - 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; et al. (MIE, 2023)

Continual Pre-Training of Large Language Models: How to (re)warm your model? - Kshitij Gupta; Benjamin Thérien; Adam Ibrahim; Mats L. Richter; Quentin Anthony; Eugene Belilovsky; Irina Rish; Timothée Lesort (CoRR, 2023)

Würstchen: An Efficient Architecture for Large-Scale Text-to-Image Diffusion Models. - Pablo Pernias; Dominic Rampas; Mats L. Richter; Christopher Pal; Marc Aubreville (ICLR, 2024)

CarbonSense: A Multimodal Dataset and Baseline for Carbon Flux Modelling. - Matthew Fortier; Mats L. Richter; Oliver Sonnentag; Chris Pal (CoRR, 2024)

Simple and Scalable Strategies to Continually Pre-train Large Language Models. - Adam Ibrahim; Benjamin Thérien; Kshitij Gupta; Mats L. Richter; Quentin Gregory Anthony; Eugene Belilovsky; Timothée Lesort; Irina Rish (Trans. Mach. Learn. Res., 2024)

Abstract: Würstchen - An Efficient Architecture for Large-scale Text-to-image Diffusion Models. - Pablo Pernias; Dominic Rampas; Mats L. Richter; Christopher J. Pal; Marc Aubreville (Bildverarbeitung für die Medizin, 2025)

Surfer-H Meets Holo1: Cost-Efficient Web Agent Powered by Open Weights. - 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; et al. (CoRR, 2025)