1 code implementation • 11 Apr 2024 • Julia Linhart, Gabriel Victorino Cardoso, Alexandre Gramfort, Sylvain Le Corff, Pedro L. C. Rodrigues
Determining which parameters of a non-linear model could best describe a set of experimental data is a fundamental problem in science and it has gained much traction lately with the rise of complex large-scale simulators (a. k. a.
1 code implementation • NeurIPS 2023 • Julia Linhart, Alexandre Gramfort, Pedro L. C. Rodrigues
Building upon the well-known classifier two-sample test (C2ST), we introduce L-C2ST, a new method that allows for a local evaluation of the posterior estimator at any given observation.
no code implementations • 17 Nov 2022 • Julia Linhart, Alexandre Gramfort, Pedro L. C. Rodrigues
Building on the recent trend of new deep generative models known as Normalizing Flows (NF), simulation-based inference (SBI) algorithms can now efficiently accommodate arbitrary complex and high-dimensional data distributions.
