christinaheinze

backShift

Code for 'backShift', an algorithm to estimate the connectivity matrix of a directed (possibly cyclic) graph with hidden variables.

causality-course-ethz

Code used in the causality course (401-4632-15) at ETH Zurich.

christinaheinze.github.io

CompareCausalNetworks

A unified interface for the estimation of causal networks

core

TensorFlow implementation of 'Core', proposed in "Conditional Variance Penalties and Domain Shift Robustness".

latent-linear-adjustment-autoencoders

Latent Linear Adjustment autoencoders: A novel method for estimating and simulating dynamic precipitation at high resolution

learning-blackjack

Seminar in Statistics: Learning Blackjack (seminar taught at ETH Zurich in spring 2016)

loco-lib

A library for distributed L2-penalised estimation problems, implemented in Scala&Spark.

mvs-autoencoders

Code for (variational) autoencoders, provided for the lecture Multivariate Statistics at ETH Zurich in spring 2017.

nonlinearICP-and-CondIndTests

Code for a variety of nonlinear conditional independence tests and 'nonlinear Invariant Causal Prediction' to estimate the causal parents of a given target variable from data collected in different experimental or environmental conditions, extending 'Invariant Causal Prediction' from Peters, Buehlmann and Meinshausen (2016) to nonlinear settings.

christinaheinze/CompareCausalNetworks

A unified interface for the estimation of causal networks

christinaheinze/causality-course-ethz

Code used in the causality course (401-4632-15) at ETH Zurich.

christinaheinze/nonlinearICP-and-CondIndTests

Code for a variety of nonlinear conditional independence tests and 'nonlinear Invariant Causal Prediction' to estimate the causal parents of a given target variable from data collected in different experimental or environmental conditions, extending 'Invariant Causal Prediction' from Peters, Buehlmann and Meinshausen (2016) to nonlinear settings.

christinaheinze/core

TensorFlow implementation of 'Core', proposed in "Conditional Variance Penalties and Domain Shift Robustness".

christinaheinze/backShift

Code for 'backShift', an algorithm to estimate the connectivity matrix of a directed (possibly cyclic) graph with hidden variables.

christinaheinze/latent-linear-adjustment-autoencoders

Latent Linear Adjustment autoencoders: A novel method for estimating and simulating dynamic precipitation at high resolution

christinaheinze/loco-lib

A library for distributed L2-penalised estimation problems, implemented in Scala&Spark.

christinaheinze/mvs-autoencoders

Code for (variational) autoencoders, provided for the lecture Multivariate Statistics at ETH Zurich in spring 2017.

christinaheinze/learning-blackjack

Seminar in Statistics: Learning Blackjack (seminar taught at ETH Zurich in spring 2016)

christinaheinze/christinaheinze.github.io

christinaheinze/vagan-code

Tensorflow implementation of 'Visual Feature Attribution using Wasserstein GANs'