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abcdistances.jl

Performs approximate Bayesian computation (ABC) using various distance functions

arcade

ARCADE Biological Modeling Framework

awesome-bayesian-deep-learning

A curated list of resources dedicated to bayesian deep learning

awesome-network-analysis

A curated list of awesome network analysis resources.

bayes-nn

Lecture notes on Bayesian deep learning

bayesiandifferentiableprogramming

deepmd-kit

A deep learning package for many-body potential energy representation and molecular dynamics

diffeq

Basic Ordinary Differential Equation solvers

discretizers.jl

A Julia package for data discretization and label maps

dynamicinfluencenetworks

Interactive visualization of Dynamic Influence Networks (DINs) for rule-based models. Click below for the online software demo (DIN-Viz) showing a simple dataset; load in data/miniKaiProb3.zip to explore a larger example dataset.

egfrd

enhanced Green's Function Reaction Dynamics

eqnfree

In this repository, I am working on a framework that contains various methods from equation-free modeling, especially bifurcation analysis and projective integration.

geopython

Notebooks and libraries for spatial/geo Python explorations

gln

graphplot.jl

Graph visualization for Julia.

hypernetx

Python package for hypergraph analysis and visualization.

igraph

Library for the analysis of networks

kcws

Deep Learning Chinese Word Segment

lammps-sys

Rust bindgen wrapper (and static lib builder) for LAMMPS

lightgraphs.jl

An optimized graphs package for Julia

machinelearning

Machine learning resources

machinelearning_python

机器学习算法python实现

mechsearch

nci-doe-collab-pilot2-mummi

Multiscale Machine-learned Modeling Infrastructure (MuMMI) is a methodology that the Pilot 2 team has developed to study the interaction of active KRAS with the plasma membrane (and related phenomena) on very large temporal and spatial scales.

ndlib

Network Diffusion Library - (for NetworkX and iGraph)

network_diffusion

networkx

Official NetworkX source code repository.

pakman

A modular, efficient and portable tool for running parallel approximate Bayesian computation algorithms.

pinns

Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations

probability_cheatsheet

A comprehensive 10-page probability cheatsheet that covers a semester's worth of introduction to probability.