abitofalchemy
Graph data scientist, AI & hardware engineer - Working on design solutions using SOTA methods from NLP, Graph NN, and DL models.
DeloitteIndiana
abitofalchemy's Stars
amueller/word_cloud
A little word cloud generator in Python
deepchem/deepchem
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
igraph/igraph
Library for the analysis of networks
opencypher/openCypher
Specification of the Cypher property graph query language
nkahmed/PGD
A Parallel Graphlet Decomposition Library for Large Graphs
somacdivad/grinpy
A NetworkX extension for calculating graph invariants.
eyaylali/sent
Hackbright 4-week Capstone Project
satyakisikdar/CNRG
Code release for the paper "Modeling Graphs with Vertex Replacement Grammars" by Sikdar et al.
suryavb95/Image-Segmentation-spanning-trees
Efficient graph-based image segmentation algorithm that finds evidence of a boundary between two regions using a graph-based segmentation of the image, described in a paper by Felzenszwalb and Huttenlocher
ContentMine/Chicago-20141114
ContentMine workshop in Chicago (US), November 14th 2014
ElSeidy/GraMi
GraMi is a novel framework for frequent subgraph mining in a single large graph, GraMi outperforms existing techniques by 2 orders of magnitudes. GraMi supports finding frequent subgraphs as well as frequent patterns, Compared to subgraphs, patterns offer a more powerful version of matching that captures transitive interactions between graph nodes (like friend of a friend) which are very common in modern applications. Also, GraMi supports user-defined structural and semantic constraints over the results, as well as approximate results. For more details, check our paper: Mohammed Elseidy, Ehab Abdelhamid, Spiros Skiadopoulos, and Panos Kalnis. GRAMI: Frequent Subgraph and Pattern Mining in a Single Large Graph. PVLDB, 7(7):517-528, 2014.
IBMStreams/sample.netflow
Netflow sample