Marius Hobbhahn

According to our database, Marius Hobbhahn authored at least 8 papers between 2020 and 2024.

Collaborative distances:

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

2024

Black-Box Access is Insufficient for Rigorous AI Audits.

Stephen Casper, Carson Ezell, Charlotte Siegmann, Noam Kolt, Taylor Lynn Curtis, Benjamin Bucknall, Andreas Alexander Haupt, Kevin Wei, Jérémy Scheurer, Marius Hobbhahn, Lee Sharkey, Satyapriya Krishna, Marvin Von Hagen, Silas Alberti, Alan Chan, Qinyi Sun, Michael Gerovitch, David Bau, Max Tegmark, David Krueger, Dylan Hadfield-Menell

CoRR, 2024

2023

Technical Report: Large Language Models can Strategically Deceive their Users when Put Under Pressure.

Jérémy Scheurer, Mikita Balesni, Marius Hobbhahn

CoRR, 2023

2022

Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning.

Pablo Villalobos, Jaime Sevilla, Lennart Heim, Tamay Besiroglu, Marius Hobbhahn, Anson Ho

CoRR, 2022

Machine Learning Model Sizes and the Parameter Gap.

Pablo Villalobos, Jaime Sevilla, Tamay Besiroglu, Lennart Heim, Anson Ho, Marius Hobbhahn

CoRR, 2022

Fast predictive uncertainty for classification with Bayesian deep networks.

Marius Hobbhahn, Agustinus Kristiadi, Philipp Hennig

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Compute Trends Across Three Eras of Machine Learning.

Jaime Sevilla, Lennart Heim, Anson Ho, Tamay Besiroglu, Marius Hobbhahn, Pablo Villalobos

Proceedings of the International Joint Conference on Neural Networks, 2022

2021

Laplace Matching for fast Approximate Inference in Generalized Linear Models.

Marius Hobbhahn, Philipp Hennig

CoRR, 2021

2020

Sequence Classification using Ensembles of Recurrent Generative Expert Modules.

Marius Hobbhahn, Martin V. Butz, Sarah Fabi, Sebastian Otte

Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020