457 skills found · Page 5 of 16
nec-research / TKG Forecasting EvaluationEvaluation of Methods for Temporal Knowledge Graph Forecasting
codefilarete / StalactiteStalactite is a non-intrusive ORM thanks to Java method reference usage, it also promotes bounded-context entity graphs by forbidding lazy initialization
bio-ontology-research-group / Multi Drug EmbeddingMethod for drug repurposing from knowledge graphs and literature
ARUN-S-CODER / Table Recognition ProjectExtract tables from invoice images, process text using OCR, extract entities and relationships using LLM and traditional methods, and construct a visual knowledge graph.
azizka / SampbiasSampbias is a method and tool to 1) visualize the distribution of occurrence records and species in any user-provided dataset, 2) quantify the biasing effect of geographic features related to human accessibility, such as proximity to cities, rivers or roads, and 3) create publication-level graphs of these biasing effects in space.
jar-analyzer / Jar Analyzer EngineJava bytecode analysis engine built on ASM, extracts method call graphs, inheritance trees, Spring routes, and string constants from JAR/WAR into SQLite. AI-friendly output for security auditing.
narayanps / NolinearTimeSeriesAnalysisThe codes in the toolbox can be used to perform nonlinear time series analysis on single(or multi) channel data. This is done by mapping the single channel data to phase space representation using Taken's embedding theorem (compute_psv.m). The parameters - optimal delay and dimension are estimated using first minimum of MI (compute_tau.m) and FNN method (compute_dim) respectively. The recurrence network can be constructed from the phase space vector using ComputeRecurrenceNetwork_ANN.m or ComputeRecurrenceNetwork_fixedRR.m. The topology of the RN can be further analysed using graph theoreticl quantifiers (you need BCT toolbox for this). One can also compute the complexity-entrropy plane using get_mpr_complexity.m for which the ordinal patterns are computed using get_ordinal_pattern_dist.m (see the function descp for more details). Also, the tool box contains python codes to generate variety of uni(or multi) variate surrogate data.
bluer555 / KernelGCNCodes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs
cmavro / Awesome Unsupervised GnnsList of unsupervised (self-supervised) graph neural network (GNN) methods.
ppope / Explain GraphsCode for "Explainability methods for graph convolutional neural networks" - PE Pope*, S Kolouri*, M Rostami, CE Martin, H Hoffmann (CVPR 2019)
shiningxy / ShipRouteRLThe Custom Gridworld and Environment Demo of Ship Route Planning with Reinforcement Learning. The reinforcement learning based on Qlearning method is realized. Q tables can be saved. Support documentation of training sessions. Support the display of result graphs
BigRoy / NodexThis package defines a wrapping functionality to create and manage mathematical node connections in Maya through Python scripting. The ease of access and method of using this will help to write readable and maintainable code for node based graphs that require a lot of mathematical processing.
BioMedicalBigDataMiningLab / GraphCDRGraphCDR: A graph neural network method with contrastive learning for cancer drug response prediction
HipGraph / FusedMMImplementation of FusedMM method for IPDPS 2021 paper titled "FusedMM: A Unified SDDMM-SpMM Kernel for Graph Embedding and Graph Neural Networks"
pbielak / Graph Barlow TwinsThe official implementation of the Graph Barlow Twins method with the experimental pipeline
PlayerIO / Facebook Graph As3A thin Facebook Graph client in ActionScript 3 which closely mirrors the methods in the official Javascript Facebook SDK
MurpheyLab / DPGOOfficial Implementation of "Majorization Minimization Methods for Distributed Pose Graph Optimization"
gnthibault / Optimisation PythonA set of notebooks related to convex optimization, variational inference and numerical methods for signal processing, machine learning, deep learning, graph analysis, bayesian programming, statistics or astronomy.
Zarachodar / GAEforBTCThis is the implementation for the Detection and Protection methods described in the paper: "Graph-Based Covert Transaction Detection and Protection in Blockchain".
utkarshtandon / GMCP Tracker Python ImplementationThis human tracking algorithm is a Python implementation of the paper "GMCP-Tracker: Global Multi-object Tracking Using Generalized Minimum Clique Graphs". The algorithm attempts to solve the optimization problem of human tracking data association which in our methods minimizes motion and appearance cost in order to generate a tracklet of a human even if occlusion exists.
