| Continual Pre-Training of Large Language Models: How to (re) warm your model? K Gupta, B Thérien, A Ibrahim, ML Richter, Q Anthony, E Belilovsky, I Rish, ... S-FoMo Workshop at the 40th International Conference on Machine Learning, 2023 | 52 | 2023 |
| Würstchen: An Efficient Architecture for Large-Scale Text-to-Image Diffusion Models P Pernias, D Rampas, ML Richter, C Pal, M Aubreville (Top 1.2%, Oral) The Twelfth International Conference on Learning …, 2024 | 43* | 2024 |
| Simple and Scalable Strategies to Continually Pre-train Large Language Models A Ibrahim, B Thérien, K Gupta, ML Richter, Q Anthony, T Lesort, ... Transactions in Machine Learning Research (https://openreview.net/forum?id …, 2024 | 34 | 2024 |
| (Input) size matters for CNN classifiers ML Richter, W Byttner, U Krumnack, A Wiedenroth, L Schallner, J Shenk Artificial Neural Networks and Machine Learning–ICANN 2021: 30th …, 2021 | 30 | 2021 |
| Should you go deeper? optimizing convolutional neural network architectures without training ML Richter, J Schöning, A Wiedenroth, U Krumnack 2021 20th IEEE International Conference on Machine Learning and Applications …, 2021 | 21 | 2021 |
| AI-Based Crop Rotation for Sustainable Agriculture Worldwide J Schöning, ML Richter 2021 IEEE Global Humanitarian Technology Conference (GHTC), 142-146, 2021 | 15 | 2021 |
| Receptive field analysis for optimizing convolutional neural network architectures without training ML Richter, J Schöning, A Wiedenroth, U Krumnack Deep Learning Applications, Volume 4, 235-261, 2022 | 10* | 2022 |
| Spectral analysis of latent representations J Shenk, ML Richter, A Arpteg, M Huss arXiv preprint arXiv:1907.08589, 2019 | 9 | 2019 |
| Automatic wound type classification with convolutional neural networks L Malihi, J Hüsers, ML Richter, M Moelleken, M Przysucha, D Busch, ... Advances in Informatics, Management and Technology in Healthcare, 281-284, 2022 | 7 | 2022 |
| Feature space saturation during training ML Richter, J Shenk, W Byttner, A Arpteg, M Huss British Machine Vision Conference 2021, 2021 | 6 | 2021 |
| An image based object recognition system for wound detection and classification of diabetic foot and venous leg ulcers J Hüsers, M Moelleken, ML Richter, M Przysucha, L Malihi, D Busch, ... Challenges of Trustable AI and Added-Value on Health, 63-67, 2022 | 5 | 2022 |
| Exploring the Properties and Evolution of Neural Network Eigenspaces during Training ML Richter, L Malihi, AKP Windler, U Krumnack MVIP 2022, 2022 | 1 | 2022 |
| Delve: Neural Network Feature Variance Analysis J Shenk, ML Richter, W Byttner Journal of Open Source Software 69 (7), 3992, 2022 | 1 | 2022 |
| CarbonSense: A Multimodal Dataset and Baseline for Carbon Flux Modelling M Fortier, ML Richter, O Sonnentag, C Pal arXiv preprint arXiv:2406.04940, 2024 | | 2024 |
| Can Synthetic Images Improve CNN Performance in Wound Image Classification? HJ Malihi L, Hübner U, Richter ML, Moelleken M, Przysucha M, Busch D ... Caring is Sharing – Exploiting the Value in Data for Health and Innovation …, 2023 | | 2023 |
| Analyzing the Inference Process in Deep Convolutional Neural Networks using Principal Eigenfeatures, Saturation and Logistic Regression Probes ML Richter, L Malihi, AKP Windler, U Krumnack Journal of Applied Research in Electrical Engineering 2 (1), 1-10, 2023 | | 2023 |
| Towards Efficient Convolutional Neural Architecture Design: Exploring the Properties of Neural Architectures Using Spectral Decomposition and Logistic Regression Probes ML Richter University of Osnabrück, 2022 | | 2022 |
| Towards efficient convolutional neural architecture design ML Richter Dissertation - University of Osnabrück, 2022 | | 2022 |
| Automatic wound type classification with convolutional neural networks L Malihi, J Hüsers, ML Richter, M Moelleken, M Przysucha, D Busch, ... Advances in Informatics, Management and Technology in Healthcare, 281-284, 2022 | | 2022 |
| Go with the Flow: the distribution of information processing in multi-path networks ML Richter, K Shah, A Wiedenroth, S Bachu, U Krumnack International Conference on Learning Representations (ICLR) 2022 (Workshop), 2021 | | 2021 |
