Oxford Machine Learning (OxfordML)

Oxford Machine Learning

OxfordML

Geek Repo

Software and papers from the machine learning research group in the department of engineering science at the university of Oxford.

Location:Oxford

Home Page:http://www.robots.ox.ac.uk/~parg/

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Oxford Machine Learning's repositories

GPz

GPz 2.0: Heteroscedastic Gaussian processes for uncertain and incomplete data

bayesquad

Library for Bayesian Quadrature

Language:PythonLicense:MITStargazers:30Issues:26Issues:1

fault-bucket.m

Matlab code for fault and anomaly detection, drawn from MA Osborne, R Garnett, K Swersky, and N de Freitas. Prediction and Fault Detection of Environmental Signals with Uncharacterised Faults. (2012). AAAI Conference on Artificial Intelligence (AAAI 2012).

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wsabi

Minimal implementation of WSABI_L and WSABI_M in MATLAB.

Language:MatlabLicense:GPL-2.0Stargazers:7Issues:17Issues:0
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mgp

An implementation of the MGP from Garnett, et al., "Active Learning of Linear Embeddings for Gaussian Processes," UAI 2014.

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Fair_Regression

Group Fairness constraints for Decision Trees and Regression Models.

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MUBs_TraceEstimators

A python implementation of the MUBs Stochastic Trace Estimator.

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python_mgp

Marginal MGP implementation in python. Based on Garnett, R., Osborne, M., and Hennig, P. Active Learning of Linear Embeddings for Gaussian Processes. (2014).

Language:PythonLicense:GPL-2.0Stargazers:2Issues:21Issues:0

commDetNMF

Code for paper: Overlapping Community Detection via Nonnegative Matrix Factorization

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ENPG

Extraction of Narratives from a Provenance Graph. An implementation of the subgraph-matching algorithm by Ebden et al, for HAIDM/AAMAS 2015

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GeneralNetworkTools

Contains a collection of general network analysis tools I have been using during my D.Phil. For more advanced operations, see the comDetNMF, BOMP and GMMevents

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GMMevents

Code for paper: Inferring social network structure in ecological systems from spatio-temporal data streams

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pyIBCC

A Bayesian method for combining crowdsourced classifications, e.g. for citizen science projects. The default class, ibcc.py provides a variational Bayes algorithm for Independent Bayesian Classifier Combination.

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