Clint P. George (clintpgeorge)

clintpgeorge

Geek Repo

Company:Indian Institute of Technology Goa

Location:Goa, India

Home Page:https://clintpgeorge.github.io

Twitter:@clintpgeorge

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Clint P. George's starred repositories

jmlr-style-file

LaTeX style file for the Journal of Machine Learning Research

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change-tutorial

Materials for the useR2017 tutorial on changepoint detection

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sparse-variational-bnn

Code for Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee (NeurIPS 20)

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chemCal

Calibration Functions for Analytical Chemistry

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ProbBayes

R package for the text Probability and Bayesian Modeling by Jim Albert and Monika Hu

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onlineldavb

Online variational Bayes for latent Dirichlet allocation (LDA)

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30-Days-of-Python

Learn Python for the next 30 (or so) Days.

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AI_Curriculum

Open Deep Learning and Reinforcement Learning lectures from top Universities like Stanford, MIT, UC Berkeley.

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COVID-19-Change-Point-Detection

Code for reproducing results in COVID-19 data.

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cancer-data

TCGA data acquisition and processing for Project Cognoma

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python-ternary

:small_red_triangle: Ternary plotting library for python with matplotlib

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tiLDA

Multithreaded implementation of the variational inference and learning in tree-informed LDA

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LaTeX-Topic-Model-Menagerie

I'm about to take the time to make LaTeX plate diagrams for a few topic models. There's no reason I can see for more than one person to do this, so please use this in your papers. When you make new ones, send me a pull request, and we can save everyone a bunch of time.

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tikz-bayesnet

TikZ library for drawing Bayesian networks, graphical models and (directed) factor graphs in LaTeX.

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topic-models

Topic modelling software using non-parametric methods

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mglda

mg-lda with gibbs sampling です。

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pymc2

THIS IS THE **OLD** PYMC PROJECT (VERSION 2). PLEASE USE PYMC INSTEAD:

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streaming_vb

This is code associated with the paper: Broderick, T, Boyd, N, Wibisono, A, Wilson, AC, and Jordan, MI. Streaming variational Bayes. Neural Information Processing Systems, 2013. papers.nips.cc/paper/4980-streaming-variational-bayes.pdf

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ediscovery

Active Topic Learning based Legal eDiscovery

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grisham

We are looking at ways of modeling paper and user preferences.

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jProcessing

Japanese Natural Langauge Processing Libraries

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