blei-lab Goto Github PK
Name: Blei Lab
Type: Organization
Bio: We are malleable but resistant to corrosion.
Location: New York, NY
Name: Blei Lab
Type: Organization
Bio: We are malleable but resistant to corrosion.
Location: New York, NY
Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)
Software and data for "Using Text Embeddings for Causal Inference"
Implements supervised topic models with a categorical response.
collaborative topic modeling
Context Selection for Embedding Models
This implements variational inference for the correlated topic model.
Collaborative modeling for recommendation. Implements variational inference for a collaborative topic models. These models recommend items to users based on item content and other users' ratings.
Deep exponential families (DEFs)
This implements the discrete infinite logistic normal, a Bayesian nonparametric topic model that finds correlated topics.
This implements topics that change over time (Dynamic Topic Models) and a model of how individual documents predict that change.
Dynamic version of Poisson Factorization (dPF). dPF captures the changing interest of users and the evolution of items over time according to user-item ratings.
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
Tool for visualizing and browsing over data point embeddings
Exposure Matrix Factorization: modeling user exposure in recommendation
Discussion of Durante et al for JSM 2017. Includes factorial network model generalization.
Hierarchical Dirichlet processes. Topic models where the data determine the number of topics. This implements Gibbs sampling.
This implements hierarchical latent Dirichlet allocation, a topic model that finds a hierarchy of topics. The structure of the hierarchy is determined by the data.
Latent Dirichlet allocation (LDA) with bumping variational inference.
This is a C implementation of variational EM for latent Dirichlet allocation (LDA), a topic model for text or other discrete data.
Online inference for the Hierarchical Dirichlet Process. Fits hierarchical Dirichlet process topic models to massive data. The algorithm determines the number of topics.
Online variational Bayes for latent Dirichlet allocation (LDA)
The pdf and LaTeX for each paper (and sometimes the code and data used to generate the figures).
The old version of the latent Dirichlet allocation package for R
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.