4 papers
Follow the Energy, Find the Path: Riemannian Metrics from Energy-Based Models
Louis Béthune, David Vigouroux, Yilun Du +3
What is the shortest path between two data points lying in a high-dimensional space? While the answer is trivial in Euclidean geometry, it becomes significantly more complex when t…
Deep Sturm--Liouville: From Sample-Based to 1D Regularization with Learnable Orthogonal Basis Functions
David Vigouroux, Joseba Dalmau, Louis Béthune +1
Although Artificial Neural Networks (ANNs) have achieved remarkable success across various tasks, they still suffer from limited generalization. We hypothesize that this limitation…
Archetypal SAE: Adaptive and Stable Dictionary Learning for Concept Extraction in Large Vision Models
Thomas Fel, Ekdeep Singh Lubana, Jacob S. Prince +7
Sparse Autoencoders (SAEs) have emerged as a powerful framework for machine learning interpretability, enabling the unsupervised decomposition of model representations into a dicti…
ConSim: Measuring Concept-Based Explanations' Effectiveness with Automated Simulatability
Antonin Poché, Alon Jacovi, Agustin Martin Picard +2
Concept-based explanations work by mapping complex model computations to human-understandable concepts. Evaluating such explanations is very difficult, as it includes not only the…