83 citations · 128 across the 10 of their papers we have counts for
3 papers · 2 filters
Learning Functional Causal Models with Generative Neural Networks
Olivier Goudet, Diviyan Kalainathan, Philippe Caillou +3
We introduce a new approach to functional causal modeling from observational data, called Causal Generative Neural Networks (CGNN). CGNN leverages the power of neural networks to l…
The Kernel Mixture Network: A Nonparametric Method for Conditional Density Estimation of Continuous Random Variables
Luca Ambrogioni, Umut Güçlü, Marcel A. J. van Gerven +1
This paper introduces the kernel mixture network, a new method for nonparametric estimation of conditional probability densities using neural networks. We model arbitrarily complex…
Estimating Nonlinear Dynamics with the ConvNet Smoother
Luca Ambrogioni, Umut Güçlü, Eric Maris +1
Estimating the state of a dynamical system from a series of noise-corrupted observations is fundamental in many areas of science and engineering. The most well-known method, the Ka…