1.6k citations · 12.4k across the 394 of their papers we have counts for
6 papers · 2 filters
Learning Dynamical Systems using Local Stability Priors
Arash Mehrjou, Andrea Iannelli, Bernhard Schölkopf
A coupled computational approach to simultaneously learn a vector field and the region of attraction of an equilibrium point from generated trajectories of the system is proposed.…
Geometrically Enriched Latent Spaces
Georgios Arvanitidis, Søren Hauberg, Bernhard Schölkopf
A common assumption in generative models is that the generator immerses the latent space into a Euclidean ambient space. Instead, we consider the ambient space to be a Riemannian m…
Causal Feature Selection via Orthogonal Search
Ashkan Soleymani, Anant Raj, Stefan Bauer +2
The problem of inferring the direct causal parents of a response variable among a large set of explanatory variables is of high practical importance in many disciplines. However, e…
Relative gradient optimization of the Jacobian term in unsupervised deep learning
Luigi Gresele, Giancarlo Fissore, Adrián Javaloy +2
Learning expressive probabilistic models correctly describing the data is a ubiquitous problem in machine learning. A popular approach for solving it is mapping the observations in…
Towards causal generative scene models via competition of experts
Julius von Kügelgen, Ivan Ustyuzhaninov, Peter Gehler +2
Learning how to model complex scenes in a modular way with recombinable components is a pre-requisite for higher-order reasoning and acting in the physical world. However, current…
Testing Goodness of Fit of Conditional Density Models with Kernels
Wittawat Jitkrittum, Heishiro Kanagawa, Bernhard Schölkopf
We propose two nonparametric statistical tests of goodness of fit for conditional distributions: given a conditional probability density function and a joint sample, decid…