Marius Hobbhahn

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 15

Top Topics

Generalized Linear Models

Machine Learning

Dempster Shafer

Top Venues

Publications

Stephen Casper, Carson Ezell, Charlotte Siegmann, Noam Kolt, Taylor Lynn Curtis, Benjamin Bucknall, Andreas A. 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
Black-Box Access is Insufficient for Rigorous AI Audits. FAccT (2024)
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
Black-Box Access is Insufficient for Rigorous AI Audits. CoRR (2024)
Lucius Bushnaq, Stefan Heimersheim, Nicholas Goldowsky-Dill, Dan Braun, Jake Mendel, Kaarel Hänni, Avery Griffin, Jörn Stöhler, Magdalena Wache, Marius Hobbhahn
The Local Interaction Basis: Identifying Computationally-Relevant and Sparsely Interacting Features in Neural Networks. CoRR (2024)
Rudolf Laine, Bilal Chughtai, Jan Betley, Kaivalya Hariharan, Jérémy Scheurer, Mikita Balesni, Marius Hobbhahn, Alexander Meinke, Owain Evans
Me, Myself, and AI: The Situational Awareness Dataset (SAD) for LLMs. CoRR (2024)
Lucius Bushnaq, Jake Mendel, Stefan Heimersheim, Dan Braun, Nicholas Goldowsky-Dill, Kaarel Hänni, Cindy Wu, Marius Hobbhahn
Using Degeneracy in the Loss Landscape for Mechanistic Interpretability. CoRR (2024)
Martina Contisciani, Marius Hobbhahn, Eleanor A. Power, Philipp Hennig, Caterina De Bacco
Flexible inference in heterogeneous and attributed multilayer networks. CoRR (2024)
Jérémy Scheurer, Mikita Balesni, Marius Hobbhahn
Technical Report: Large Language Models can Strategically Deceive their Users when Put Under Pressure. CoRR (2023)
Pablo Villalobos, Jaime Sevilla, Lennart Heim, Tamay Besiroglu, Marius Hobbhahn, Anson Ho
Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning. CoRR (2022)
Pablo Villalobos, Jaime Sevilla, Tamay Besiroglu, Lennart Heim, Anson Ho, Marius Hobbhahn
Machine Learning Model Sizes and the Parameter Gap. CoRR (2022)
Marius Hobbhahn, Agustinus Kristiadi, Philipp Hennig
Fast predictive uncertainty for classification with Bayesian deep networks. UAI (2022)
Jaime Sevilla, Lennart Heim, Anson Ho, Tamay Besiroglu, Marius Hobbhahn, Pablo Villalobos
Compute Trends Across Three Eras of Machine Learning. CoRR (2022)
Jaime Sevilla, Lennart Heim, Anson Ho, Tamay Besiroglu, Marius Hobbhahn, Pablo Villalobos
Compute Trends Across Three Eras of Machine Learning. IJCNN (2022)
Marius Hobbhahn, Philipp Hennig
Laplace Matching for fast Approximate Inference in Generalized Linear Models. CoRR (2021)
Marius Hobbhahn, Martin V. Butz, Sarah Fabi, Sebastian Otte
Sequence Classification using Ensembles of Recurrent Generative Expert Modules. ESANN (2020)
Marius Hobbhahn, Agustinus Kristiadi, Philipp Hennig
Fast Predictive Uncertainty for Classification with Bayesian Deep Networks. CoRR (2020)