Bayesian Modeling and Probabilistic Programming in Python
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Updated
Jun 11, 2024 - Python
Bayesian Modeling and Probabilistic Programming in Python
Variational Inference of Polygenic Risk Scores
Implementing Bayesian neural networks to minimize the amortization gap in VAEs, investigating their potential to approximate the optimal solution to the amortization interpolation problem in PyTorch.
Personal Website with Blogposts, Achievements and Ideas
The political text ideology extraction tool is a one dimensional "ideal point" projector that utilizes variational encoding methods to quantify an author's political leaning.
CmdStanR: the R interface to CmdStan
Detecting mutational signatures via bayesian inference and a reference catalog
High-performance reactive message-passing based Bayesian inference engine
Gaussian processes in TensorFlow
Variational Inference for Multiply-Reported social network data https://doi.org/10.1093/jrsssa/qnac004
Deep universal probabilistic programming with Python and PyTorch
Preheat your MCMC
c++ library for parallel and distributed estimation of mixture model components using variational inference.
Thesis projects
Code for the paper: Mixed Models with Multiple Instance Learning
Demultiplexing pooled scRNA-seq data with or without genotype reference
WISER: multimodal variational inference for full-waveform inversion without dimensionality reduction
A probabilistic framework in PyTorch for phylogenetic models
A set of notebooks related to convex optimization, variational inference and numerical methods for signal processing, machine learning, deep learning, graph analysis, bayesian programming, statistics or astronomy.
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