Structural learning. - Dan Braun (Scholarpedia, 2013)

Construction and Elicitation of a Black Box Model in the Game of Bridge. - Véronique Ventos; Daniel Braun 007; Colin Deheeger; Jean Pierre Desmoulins; Jean Baptiste Fantun; Swann Legras; Alexis Rimbaud; Céline Rouveirol; Henry Soldano (CoRR, 2020)

Interpreting Neural Networks through the Polytope Lens. - Sid Black; Lee Sharkey; Léo Grinsztajn; Eric Winsor; Dan Braun; Jacob Merizian; Kip Parker; Carlos Ramón Guevara; Beren Millidge; Gabriel Alfour; Connor Leahy (CoRR, 2022)

Identifying Functionally Important Features with End-to-End Sparse Dictionary Learning. - Dan Braun; Jordan Taylor; Nicholas Goldowsky-Dill; Lee Sharkey (NeurIPS, 2024)

Using Degeneracy in the Loss Landscape for Mechanistic Interpretability. - Lucius Bushnaq; Jake Mendel; Stefan Heimersheim; Dan Braun; Nicholas Goldowsky-Dill; Kaarel Hänni; Cindy Wu; Marius Hobbhahn (CoRR, 2024)

The Local Interaction Basis: Identifying Computationally-Relevant and Sparsely Interacting Features in Neural Networks. - Lucius Bushnaq; Stefan Heimersheim; Nicholas Goldowsky-Dill; Dan Braun; Jake Mendel; Kaarel Hänni; Avery Griffin; Jörn Stöhler; Magdalena Wache; Marius Hobbhahn (CoRR, 2024)

Towards evaluations-based safety cases for AI scheming. - Mikita Balesni; Marius Hobbhahn; David Lindner; Alexander Meinke; Tomek Korbak; Joshua Clymer; Buck Shlegeris; Jérémy Scheurer; Charlotte Stix; Rusheb Shah; Nicholas Goldowsky-Dill; Dan Braun; et al. (CoRR, 2024)

Interpretability in Parameter Space: Minimizing Mechanistic Description Length with Attribution-based Parameter Decomposition. - Dan Braun; Lucius Bushnaq; Stefan Heimersheim; Jake Mendel; Lee Sharkey (CoRR, 2025)

Parameterized Synthetic Text Generation with SimpleStories. - Lennart Finke; Thomas Dooms; Mat Allen; Juan Diego Rodriguez; Noa Nabeshima; Dan Braun (CoRR, 2025)

Stochastic Parameter Decomposition. - Lucius Bushnaq; Dan Braun; Lee Sharkey (CoRR, 2025)