richardshea Goto Github PK

jodie

A PyTorch implementation of ACM SIGKDD 2019 paper "Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks"

lantern-neurips-2019

Source code for NeurIPS 2019 paper "Learning Latent Processes from High-Dimensional Event Sequences via Efficient Sampling""

lowrankhawkes

fast low rank multivariate Hawkes processes

lspp

Latent Space Point Process Models for Dynamic Networks

madewithml

Learn how to responsibly deliver value with ML.

mesa

Mesa is an agent-based modeling framework in Python

mesa-hawkes-fireflies

Netlogo Fireflies to Mesa with Hawkes clock

ml-resources

mml-book.github.io

Companion webpage to the book "Mathematics For Machine Learning"

mpoints

A machine learning tool that implements the class of state-dependent Hawkes processes.

multiscalediscovery

networkie

Introduction to data engineering workflows for undergraduates

neural-spectral-marked-point-processes

A novel general non-stationary point process model based on neural networks.

pandas-datareader

Extract data from a wide range of Internet sources into a pandas DataFrame.

pennai

the Penn AI engine.

pml-book

"Probabilistic Machine Learning" - a book series by Kevin Murphy

probabilistic-programming-and-bayesian-methods-for-hackers

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

pylob

Fully functioning fast Limit Order Book written in Python

quantile-propagation-for-wasserstein-approximate-gaussian-processes

sbsgmest

EM-Based Estimation Routine for Stochastic Block Smooth Graphon Models - see 'Stochastic Block Smooth Graphon Model' [arXiv:2203.13304]

sgwb-graphon

Learning Graphons via Structured Gromov-Wasserstein Barycenters

sir-hawkes

SIR-Hawkes: Linking Epidemic Models and Hawkes Processes to Model Diffusions in Finite Populations

svd_article

tda-api

A TD Ameritrade API client for Python. Includes historical data for equities and ETFs, options chains, streaming order book data, complex order construction, and more.

tdgraphembed

tennis-prediction

A Machine Learning approach to predict Tennis' matches outcome to make a profitable betting strategy 🎾 📈 💸

tensorly-notebooks

Tensor methods in Python with TensorLy

theoretical-algorithms-implementation

CLRS(Introduction to Algorithms) - Python/C++/Java Implementation of all the major Algorithms in the CLRS Textbook as well as additional algorithm's covered in the University of Alberta theory Courses

tick

Module for statistical learning, with a particular emphasis on time-dependent modelling

turnout_tracker