Search Results for author: Jonathan K. Pritchard

Found 3 papers, 2 papers with code

Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling

1 code implementation7 Nov 2022 Romain Lopez, Nataša Tagasovska, Stephen Ra, Kyunghyn Cho, Jonathan K. Pritchard, Aviv Regev

Instead, recent methods propose to leverage non-stationary data, as well as the sparse mechanism shift assumption in order to learn disentangled representations with a causal semantic.

Disentanglement Domain Generalization +1

On the number of genealogical ancestors tracing to the source groups of an admixed population

no code implementations22 Oct 2022 Jazlyn A. Mooney, Lily Agranat-Tamir, Jonathan K. Pritchard, Noah A. Rosenberg

Using a mechanistic model of admixture, we characterize admixture genealogically: how many distinct ancestors from the source populations does the admixture represent?

Large-Scale Differentiable Causal Discovery of Factor Graphs

1 code implementation15 Jun 2022 Romain Lopez, Jan-Christian Hütter, Jonathan K. Pritchard, Aviv Regev

Combining this novel structural assumption with recent advances that bridge the gap between causal discovery and continuous optimization, we achieve causal discovery on thousands of variables.

Causal Discovery Causal Inference

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