Tobias Pielok

According to our database, Tobias Pielok authored at least 7 papers between 2022 and 2025.

Collaborative distances:

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

2025

Semi-Implicit Variational Inference via Kernelized Path Gradient Descent.

Tobias Pielok, Bernd Bischl, David Rügamer

CoRR, June, 2025

Revisiting Unbiased Implicit Variational Inference.

Tobias Pielok, Bernd Bischl, David Rügamer

CoRR, June, 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

2023

Multi-Objective Hyperparameter Optimization in Machine Learning - An Overview.

Florian Karl, Tobias Pielok, Julia Moosbauer, Florian Pfisterer, Stefan Coors, Martin Binder, Lennart Schneider, Janek Thomas, Jakob Richter, Michel Lang, Eduardo C. Garrido-Merchán, Jürgen Branke, Bernd Bischl

ACM Trans. Evol. Learn. Optim., December, 2023

Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges.

Bernd Bischl, Martin Binder, Michel Lang, Tobias Pielok, Jakob Richter, Stefan Coors, Janek Thomas, Theresa Ullmann, Marc Becker, Anne-Laure Boulesteix, Difan Deng, Marius Lindauer

WIREs Data. Mining. Knowl. Discov., 2023

Approximate Bayesian Inference with Stein Functional Variational Gradient Descent.

Tobias Pielok, Bernd Bischl, David Rügamer

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Multi-Objective Hyperparameter Optimization - An Overview.

Florian Karl, Tobias Pielok, Julia Moosbauer, Florian Pfisterer, Stefan Coors, Martin Binder, Lennart Schneider, Janek Thomas, Jakob Richter, Michel Lang, Eduardo C. Garrido-Merchán, Jürgen Branke, Bernd Bischl

CoRR, 2022