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Marius Hobbhahn
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2020 – today
- 2024
- [c4]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: 2254-2272 - [i11]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 abs/2401.14446 (2024) - [i10]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 abs/2405.10927 (2024) - [i9]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 abs/2405.10928 (2024) - [i8]Martina Contisciani, Marius Hobbhahn, Eleanor A. Power, Philipp Hennig, Caterina De Bacco:
Flexible inference in heterogeneous and attributed multilayer networks. CoRR abs/2405.20918 (2024) - [i7]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 abs/2407.04694 (2024) - 2023
- [i6]Jérémy Scheurer, Mikita Balesni, Marius Hobbhahn:
Technical Report: Large Language Models can Strategically Deceive their Users when Put Under Pressure. CoRR abs/2311.07590 (2023) - 2022
- [c3]Jaime Sevilla
, Lennart Heim, Anson Ho
, Tamay Besiroglu, Marius Hobbhahn, Pablo Villalobos:
Compute Trends Across Three Eras of Machine Learning. IJCNN 2022: 1-8 - [c2]Marius Hobbhahn, Agustinus Kristiadi, Philipp Hennig:
Fast predictive uncertainty for classification with Bayesian deep networks. UAI 2022: 822-832 - [i5]Jaime Sevilla, Lennart Heim, Anson Ho, Tamay Besiroglu, Marius Hobbhahn, Pablo Villalobos:
Compute Trends Across Three Eras of Machine Learning. CoRR abs/2202.05924 (2022) - [i4]Pablo Villalobos, Jaime Sevilla
, Tamay Besiroglu, Lennart Heim, Anson Ho
, Marius Hobbhahn:
Machine Learning Model Sizes and the Parameter Gap. CoRR abs/2207.02852 (2022) - [i3]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 abs/2211.04325 (2022) - 2021
- [i2]Marius Hobbhahn, Philipp Hennig:
Laplace Matching for fast Approximate Inference in Generalized Linear Models. CoRR abs/2105.03109 (2021) - 2020
- [c1]Marius Hobbhahn, Martin V. Butz, Sarah Fabi, Sebastian Otte:
Sequence Classification using Ensembles of Recurrent Generative Expert Modules. ESANN 2020: 333-338 - [i1]Marius Hobbhahn, Agustinus Kristiadi, Philipp Hennig:
Fast Predictive Uncertainty for Classification with Bayesian Deep Networks. CoRR abs/2003.01227 (2020)
Coauthor Index
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last updated on 2024-08-13 21:48 CEST by the dblp team
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