Outlier detection for categorical data
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Updated
Jul 11, 2024 - Python
Outlier detection for categorical data
Practical volume computation and sampling in high dimensions
[ICML'24W] Revisiting Random Walks for Learning on Graphs, in PyTorch
CUDA-based flow and transport simulations in DFNs
MCMC sampling algorithms for linear inverse models in R
Random walk simulation of polaron hopping via kinetic monte carlo sampling
A Random Walk Particle Tracking code for solute transport in heterogeneous aquifers
Work we did for a practical course in graph learning, organized by department Informatik 7 at RWTH University
A header-only C++ library for Monte-Carlo sampling of cylic polygons with prescribed edge lengths.
Code and dataset for our paper "Replicate, Walk, and Stop on Syntax: an Effective Neural Network Model for Aspect-Level Sentiment Classification", AAAI2020
Implementation of metaheuristic optimization methods in Python for scientific, industrial, and educational scenarios. Experiments can be executed in parallel or in a distributed fashion. Experimental results can be evaluated in various ways, including diagrams, tables, and export to Excel.
Official Pytorch implementation of NeuralWalker
Estimate flight tracks from radio-telemetry data using a Hidden Markov Model.
Fractal images with Python
Random Walk, Percolation, Ising Model, ..
A python library for metabolic networks sampling and analysis
GraphRoam is a Python library designed to efficiently generate random walks on large graphs using consumer-grade, RAM-limited hardware.
Simulate random walk and calculate ℓ1-distance between normalized degree vector and empirical frequency vector
🚶Python Library for Random Walks
Implementation of t-SNE with c++ (including the random walk version), visualization of the process of t-SNE on MNIST with python.
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