Chris Kolb

According to our database, Chris Kolb authored at least 10 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Smoothing the Edges: Smooth Optimization for Sparse Regularization Using Hadamard Overparametrization.

Chris Kolb, Christian L. Müller, Bernd Bischl, David Rügamer

Mach. Learn., April, 2026

On the Interplay of Priors and Overparametrization in Bayesian Neural Network Posteriors.

Julius Kobialka, Emanuel Sommer, Chris Kolb, Juntae Kwon, Daniel Dold, David Rügamer

CoRR, March, 2026

2025

Differentiable Sparsity via <i>D</i>-Gating: Simple and Versatile Structured Penalization.

Chris Kolb, Laetitia Frost, Bernd Bischl, David Rügamer

CoRR, September, 2025

Deep Weight Factorization: Sparse Learning Through the Lens of Artificial Symmetries.

Chris Kolb, Tobias Weber, Bernd Bischl, David Rügamer

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

How Inverse Conditional Flows Can Serve as a Substitute for Distributional Regression.

Lucas Kook, Chris Kolb, Philipp Schiele, Daniel Dold, Marcel Arpogaus, Cornelius Fritz, Philipp F. M. Baumann, Philipp Kopper, Tobias Pielok, Emilio Dorigatti, David Rügamer

Proceedings of the Uncertainty in Artificial Intelligence, 2024

Generalizing Orthogonalization for Models with Non-Linearities.

David Rügamer, Chris Kolb, Tobias Weber, Lucas Kook, Thomas Nagler

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

deepregression: A Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression.

David Rügamer, Chris Kolb, Cornelius Fritz, Florian Pfisterer, Philipp Kopper, Bernd Bischl, Ruolin Shen, Christina Bukas, Lisa Barros de Andrade e Sousa, Dominik Thalmeier, Philipp F. M. Baumann, Lucas Kook, Nadja Klein, Christian L. Müller

J. Stat. Softw., 2023

Smoothing the Edges: A General Framework for Smooth Optimization in Sparse Regularization using Hadamard Overparametrization.

Chris Kolb, Christian L. Müller, Bernd Bischl, David Rügamer

CoRR, 2023

2021

deepregression: a Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression.

David Rügamer, Ruolin Shen, Christina Bukas, Lisa Barros de Andrade e Sousa, Dominik Thalmeier, Nadja Klein, Chris Kolb, Florian Pfisterer, Philipp Kopper, Bernd Bischl, Christian L. Müller

CoRR, 2021

2020

A Unifying Network Architecture for Semi-Structured Deep Distributional Learning.

David Rügamer, Chris Kolb, Nadja Klein

CoRR, 2020