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rahulprabhakaran's Projects

bluefog icon bluefog

Distributed and decentralized training framework for PyTorch over graph

cvxpy icon cvxpy

A Python-embedded modeling language for convex optimization problems.

fracture-graphs icon fracture-graphs

Code supplement to the manuscript, "Prabhakaran et al (2021), Large-scale fracture network patterns: Insights from automated mapping in the Lilstock (Bristol Channel) limestone outcrop"

fracture_fingerprint icon fracture_fingerprint

This repository is the Code Supplement to the manuscript preprint, "Prabhakaran et al [2021], Investigating Spatial Heterogeneity within Fracture Networks using Hierarchical Clustering and Graph Distance Metrics"

graphspectrometer icon graphspectrometer

Scripts and utilities for analyzing graphs using Fiedler vectors and spectral graph theory.

insect-wing-venation-patterns icon insect-wing-venation-patterns

Code corresponding to the manuscript "A simple developmental model recapitulates complex insect wing venation patterns" PNAS 2018

machine-learning-notes icon machine-learning-notes

My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 我不间断更新的机器学习,概率模型和深度学习的讲义(2000+页)和视频链接

mesa icon mesa

Mesa is an agent-based modeling framework in Python

ogs5 icon ogs5

OpenGeoSys THM/C simulator version 5

openpnm icon openpnm

A Python package for performing pore network modeling of porous media

osemosys icon osemosys

OSeMOSYS - the Open Source Energy Modelling System

pinns icon pinns

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

pmtk3 icon pmtk3

Probabilistic Modeling Toolkit for Matlab/Octave.

precice icon precice

A coupling library for partitioned multi-physics simulations, including, but not restricted to fluid-structure interaction and conjugate heat transfer simulations.

pypsa icon pypsa

PyPSA: Python for Power System Analysis

raven icon raven

RAVEN is a flexible and multi-purpose probabilistic risk analysis, validation and uncertainty quantification, parameter optimization, model reduction and data knowledge-discovering framework.

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