DORA: Exploring Outlier Representations in Deep Neural Networks. - Kirill Bykov; Mayukh Deb; Dennis Grinwald; Klaus-Robert Müller; Marina M.-C. Höhne (Trans. Mach. Learn. Res., 2023)

Visualizing the Diversity of Representations Learned by Bayesian Neural Networks. - Dennis Grinwald; Kirill Bykov; Shinichi Nakajima; Marina M.-C. Höhne (Trans. Mach. Learn. Res., 2023)

FedZero: Leveraging Renewable Excess Energy in Federated Learning. - Philipp Wiesner; Ramin Khalili; Dennis Grinwald; Pratik Agrawal; Lauritz Thamsen; Odej Kao (e-Energy, 2024)

Federated Learning over Connected Modes. - Dennis Grinwald; Philipp Wiesner; Shinichi Nakajima (NeurIPS, 2024)

Solution Simplex Clustering for Heterogeneous Federated Learning. - Dennis Grinwald; Philipp Wiesner; Shinichi Nakajima (CoRR, 2024)

Quality Time: Carbon-Aware Quality Adaptation for Energy-Intensive Services. - Philipp Wiesner; Dennis Grinwald; Philipp Weiß; Patrick Wilhelm; Ramin Khalili; Odej Kao (CoRR, 2024)

Carbon-Aware Quality Adaptation for Energy-Intensive Services. - Philipp Wiesner; Dennis Grinwald; Philipp Weiß; Patrick Wilhelm; Ramin Khalili; Odej Kao (e-Energy, 2025)