Borgelt, Christian

13 publications

NeurIPS 2024 Convolutional Differentiable Logic Gate Networks Felix Petersen, Hilde Kuehne, Christian Borgelt, Julian Welzel, Stefano Ermon

NeurIPS 2024 Newton Losses: Using Curvature Information for Learning with Differentiable Algorithms Felix Petersen, Christian Borgelt, Tobias Sutter, Hilde Kuehne, Oliver Deussen, Stefano Ermon

NeurIPS 2024 TrAct: Making First-Layer Pre-Activations Trainable Felix Petersen, Christian Borgelt, Stefano Ermon

ICLR 2024 Uncertainty Quantification via Stable Distribution Propagation Felix Petersen, Aashwin Ananda Mishra, Hilde Kuehne, Christian Borgelt, Oliver Deussen, Mikhail Yurochkin

ICLR 2023 ISAAC Newton: Input-Based Approximate Curvature for Newton's Method Felix Petersen, Tobias Sutter, Christian Borgelt, Dongsung Huh, Hilde Kuehne, Yuekai Sun, Oliver Deussen

NeurIPS 2022 Deep Differentiable Logic Gate Networks Felix Petersen, Christian Borgelt, Hilde Kuehne, Oliver Deussen

ICML 2022 Differentiable Top-K Classification Learning Felix Petersen, Hilde Kuehne, Christian Borgelt, Oliver Deussen

CVPR 2022 GenDR: A Generalized Differentiable Renderer Felix Petersen, Bastian Goldluecke, Christian Borgelt, Oliver Deussen

ICLR 2022 Monotonic Differentiable Sorting Networks Felix Petersen, Christian Borgelt, Hilde Kuehne, Oliver Deussen

ICML 2021 Differentiable Sorting Networks for Scalable Sorting and Ranking Supervision Felix Petersen, Christian Borgelt, Hilde Kuehne, Oliver Deussen

NeurIPS 2021 Learning with Algorithmic Supervision via Continuous Relaxations Felix Petersen, Christian Borgelt, Hilde Kuehne, Oliver Deussen

NeurIPSW 2019 $C^\infty$ Smooth Algorithmic Neural Networks for Solving Inverse Problems Felix Petersen, Christian Borgelt, Oliver Deussen

ALT 2002 Data Mining with Graphical Models Rudolf Kruse, Christian Borgelt