45 citations · 97 across the 8 of their papers we have counts for
8 papers
Decoupling Pixel Flipping and Occlusion Strategy for Consistent XAI Benchmarks
Stefan Blücher, Johanna Vielhaben, Nils Strodthoff
Feature removal is a central building block for eXplainable AI (XAI), both for occlusion-based explanations (Shapley values) as well as their evaluation (pixel flipping, PF). Howev…
Multi-dimensional concept discovery (MCD): A unifying framework with completeness guarantees
Johanna Vielhaben, Stefan Blücher, Nils Strodthoff
The completeness axiom renders the explanation of a post-hoc XAI method only locally faithful to the model, i.e. for a single decision. For the trustworthy application of XAI, in p…
Reconstructing Kernel-based Machine Learning Force Fields with Super-linear Convergence
Stefan Blücher, Klaus-Robert Müller, Stefan Chmiela
Kernel machines have sustained continuous progress in the field of quantum chemistry. In particular, they have proven to be successful in the low-data regime of force field reconst…
Sparse Subspace Clustering for Concept Discovery (SSCCD)
Johanna Vielhaben, Stefan Blücher, Nils Strodthoff
Concepts are key building blocks of higher level human understanding. Explainable AI (XAI) methods have shown tremendous progress in recent years, however, local attribution method…
PredDiff: Explanations and Interactions from Conditional Expectations
Stefan Blücher, Johanna Vielhaben, Nils Strodthoff
PredDiff is a model-agnostic, local attribution method that is firmly rooted in probability theory. Its simple intuition is to measure prediction changes while marginalizing featur…
Towards Novel Insights in Lattice Field Theory with Explainable Machine Learning
Stefan Bluecher, Lukas Kades, Jan M. Pawlowski +2
Machine learning has the potential to aid our understanding of phase structures in lattice quantum field theories through the statistical analysis of Monte Carlo samples. Available…
Reweighting Lefschetz Thimbles
Stefan Bluecher, Jan M. Pawlowski, Manuel Scherzer +4
We present a novel reweighting technique to calculate the relative weights in the Lefschetz thimble decomposition of a path integral. Our method is put to work using a one-l…
Reweighting Lefschetz Thimbles
Stefan Bluecher, Jan M. Pawlowski, Manuel Scherzer +4
One of the main challenges in simulations on Lefschetz thimbles is the computation of the relative weights of contributing thimbles. In this paper we propose a solution to that pro…