Search Results for author: Dana Pe'er

Found 4 papers, 1 papers with code

Wasserstein Wormhole: Scalable Optimal Transport Distance with Transformers

no code implementations15 Apr 2024 Doron Haviv, Russell Zhang Kunes, Thomas Dougherty, Cassandra Burdziak, Tal Nawy, Anna Gilbert, Dana Pe'er

Along with an encoder that maps distributions to embeddings, Wasserstein Wormhole includes a decoder that maps embeddings back to distributions, allowing for operations in the embedding space to generalize to OT spaces, such as Wasserstein barycenter estimation and OT interpolation.


Gradient Estimation for Binary Latent Variables via Gradient Variance Clipping

no code implementations12 Aug 2022 Russell Z. Kunes, Mingzhang Yin, Max Land, Doron Haviv, Dana Pe'er, Simon Tavaré

Gradient estimation is often necessary for fitting generative models with discrete latent variables, in contexts such as reinforcement learning and variational autoencoder (VAE) training.

A Nonparametric Multi-view Model for Estimating Cell Type-Specific Gene Regulatory Networks

no code implementations21 Feb 2019 Cassandra Burdziak, Elham Azizi, Sandhya Prabhakaran, Dana Pe'er

We present a Bayesian hierarchical multi-view mixture model termed Symphony that simultaneously learns clusters of cells representing cell types and their underlying gene regulatory networks by integrating data from two views: single-cell gene expression data and paired epigenetic data, which is informative of gene-gene interactions.


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