Search Results for author: Achille Nazaret

Found 5 papers, 2 papers with code

Variational Inference for Infinitely Deep Neural Networks

1 code implementation21 Sep 2022 Achille Nazaret, David Blei

We introduce the unbounded depth neural network (UDN), an infinitely deep probabilistic model that adapts its complexity to the training data.

Variational Inference

A joint model of unpaired data from scRNA-seq and spatial transcriptomics for imputing missing gene expression measurements

2 code implementations6 May 2019 Romain Lopez, Achille Nazaret, Maxime Langevin, Jules Samaran, Jeffrey Regier, Michael. I. Jordan, Nir Yosef

Building upon domain adaptation work, we propose gimVI, a deep generative model for the integration of spatial transcriptomic data and scRNA-seq data that can be used to impute missing genes.

Domain Adaptation Imputation

Stochastic Flows and Geometric Optimization on the Orthogonal Group

no code implementations ICML 2020 Krzysztof Choromanski, David Cheikhi, Jared Davis, Valerii Likhosherstov, Achille Nazaret, Achraf Bahamou, Xingyou Song, Mrugank Akarte, Jack Parker-Holder, Jacob Bergquist, Yuan Gao, Aldo Pacchiano, Tamas Sarlos, Adrian Weller, Vikas Sindhwani

We present a new class of stochastic, geometrically-driven optimization algorithms on the orthogonal group $O(d)$ and naturally reductive homogeneous manifolds obtained from the action of the rotation group $SO(d)$.

Metric Learning Stochastic Optimization

Stable Differentiable Causal Discovery

no code implementations17 Nov 2023 Achille Nazaret, Justin Hong, Elham Azizi, David Blei

We find that SDCD outperforms existing methods in both convergence speed and accuracy and can scale to thousands of variables.

Causal Discovery

Cannot find the paper you are looking for? You can Submit a new open access paper.