1 citations · 1 across the 4 of their papers we have counts for
4 papers
Deep Learning of Causal Structures in High Dimensions
Kai Lagemann, Christian Lagemann, Bernd Taschler +1
Recent years have seen rapid progress at the intersection between causality and machine learning. Motivated by scientific applications involving high-dimensional data, in particula…
The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up
Razvan V. Marinescu, Neil P. Oxtoby, Alexandra L. Young +93
We present the findings of "The Alzheimer's Disease Prediction Of Longitudinal Evolution" (TADPOLE) Challenge, which compared the performance of 92 algorithms from 33 international…
Ancestral causal learning in high dimensions with a human genome-wide application
Umberto Noè, Bernd Taschler, Joachim Täger +2
We consider learning ancestral causal relationships in high dimensions. Our approach is driven by a supervised learning perspective, with discrete indicators of causal relationship…
Model-based clustering in very high dimensions via adaptive projections
Bernd Taschler, Frank Dondelinger, Sach Mukherjee
Mixture models are a standard approach to dealing with heterogeneous data with non-i.i.d. structure. However, when the dimension is large relative to sample size and where…