Preprint.

NIPS 2016 Workshop on Private Multi-Party Machine Learning.

arXiv.

Preprint. bioRxiv.

Advances in Neural Information Processing Systems (NIPS) 28, 2015.

arXiv.
R package.

NIPS Workshop on Distributed Machine Learning and Matrix Computations 2014.

arXiv.
Spark package.

Unified interface for the estimation of causal networks, including the methods 'backShift', 'bivariateANM' (bivariate additive noise model),
'bivariateCAM' (bivariate causal additive model), 'CAM' (causal additive model), 'hiddenICP' (invariant causal prediction with hidden variables),
'ICP' (invariant causal prediction), 'GES' (greedy equivalence search), 'GIES' (greedy interventional equivalence search), 'LINGAM',
'PC' (PC Algorithm), 'RFCI' (really fast causal inference) and regression.

CRAN.
Github.

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

CRAN.
Github.

LOCO^{lib} implements the LOCO and DUAL-LOCO algorithms for distributed statistical estimation.

Github.

© Christina Heinze-Deml 2017. All rights reserved.