Recent Publications:

• Y. Li, M. Keuper, D. Zhang, A. Khoreva, Divide & Bind Your Attention for Improved Generative Semantic Nursing", BMVC 2023.
• J. Lukasik, M. Möller, M. Keuper, An Evaluation of Zero-Cost Proxies -- from Neural Architecture Search to Model Robustness, GCPR, 2023.
• T. Medi, J. Tayyub, M. Sarmad, F. Lindseth, M. Keuper, FullFormer: Generating Shapes inside Shapes, GCPR 2023. 
• K. Prasse, S. Jung, Y. Zhou, M. Keuper, Local Spherical Harmonics Improve Skeleton-based Hand Action Recognition, GCPR 2023.
• J. Lukasik, J. Geiping, M. Möller, M. Keuper, Differentiable Architecture Search: a One-Shot Method?, AutoML Conference workshop, 2023.
• P. Müller, A. Braun, M. Keuper, Classification robustness to common optical aberrations, ICCV2023 AROW Workshop.
• S. Agnihotri, K.V. Gandikota, J. Grabinski, P. Chandramouli, M. Keuper, On the unreasonable vulnerability of transformers for image restoration and an easy fix", ICCV2023 AROW Workshop.
• P. Gavrikov, J. Keuper, M. Keuper, An extended Benchmark Study of Human-Like Behavior under Adversarial Training, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2023.
• S. Jung, J. Lukasik, M. Keuper, Neural Architecture Design and Robustness: A Dataset, ICLR 2023.
• V. Kostyukhin, M. Keuper, I. Ibragimov, N. Owtscharenko, M. Cristinziani, Improving Primary-Vertex Reconstruction with a Minimum Cost lifted Multicut Graph Partitioning Algorithm, Journal of Instrumentation (JINST) , accepted, 2023.
• Y. Li, D. Zhang, M. Keuper, A. Khoreva, Intra-Source Style Augmentation for Improved Domain Generalization, accepted to WACV 2023.
• A. Saseendran, K. Skubsch, S. Falkner, M. Keuper, Trading-off Image Quality for Robustness is not necessary with Regularized Deterministic Autoencoders, accepted to NeurIPS 2022.
• J. Grabinski, P. Gavrikov, J. Keuper, M. Keuper, Robust Models are Less Over-Confident, accepted to NeurIPS 2022. 
• J. Lukasik, S. Jung, M. Keuper, Learning Where to Look -- Generative NAS is Surprisingly Efficient, accepted to ECCV 2022.
• J. Grabinski, S. Jung, J. Keuper, M. Keuper, FrequencyLowCut Pooling -- Plug & Play against Catastrophic Overfitting, accepted to ECCV 2022.
• J. Grabinski, J. Keuper, M. Keuper, Aliasing and adversarial robust generalizaiton of CNNs, Machine Learning,(2022)
• S. Jung, M. Keuper, Learning to solve Minimum Cost Multicuts efficiently using Edge-Weighted Graph Convolutional Neural Networks,  accepted to ECML-PKDD 2022.
• Y. Zhou, W., Xiang, C. Li, B. Wang, X. Wei, L. Zhang, M. Keuper, X., Hua, SP-VIT: Learning 2D Spatial Priors for Vision Transformers, accepted to BMVC 2022.
• S. Jung, S. Ziegler, A. Kardoost, M. Keuper, Optimizing Edge Detection for Image Segmentation with Multicut Penalties, GCPR 2022.
• E. Levinkov*, A. Kardoost*, B. Andres and M. Keuper (*equal contribution), "Higher-Order Multicuts for Geometric Model Fitting and Motion Segmentation," in IEEE Transactions on Pattern Analysis and Machine Intelligence, doi: 10.1109/TPAMI.2022.3148795.
• J. Siems, L. Zimmer, A. Zela, J. Lukasik, M. Keuper and F. Hutter, NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search, ICLR, 2022.
• A. Saseendran, K. Skubch, S. Falkner, M. Keuper, Shape your Space: A Gaussian Mixture Regularization Approach to Deterministic Autoencoders: , NeurIPS 2021.
• K. Ho, FJ Pfreundt, J Keuper, M Keuper, Estimating the Robustness of Classification Models by the Structure of the Learned Feature-Space, The AAAI-22 Workshop on Adversarial Machine Learning and Beyond, 2022
• S Jung, M Keuper, Internalized Biases in Fréchet Inception Distance, NeurIPS 2021 Workshop on Distribution Shifts, 2021.
• J Geiping, J Lukasik, M Keuper, M Moeller, DARTS for Inverse Problems: a Study on Hyperparameter Sensitivity (link is external), NeurIPS workshop on Inverse Problems, 2021.