random-sampling
There are 47 repositories under random-sampling topic.
rapidsai/raft
RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.
baggepinnen/Hyperopt.jl
Hyperparameter optimization in Julia.
antoyang/NAS-Benchmark
[ICLR 2020] NAS evaluation is frustratingly hard
daqana/dqrng
Fast Pseudo Random Number Generators for R
willGuimont/prosac
PROSAC algorithm in python
xiusu/NAS-Bench-Macro
NAS Benchmark in "Prioritized Architecture Sampling with Monto-Carlo Tree Search", CVPR2021
gstamatelat/random-sampling
A collection of algorithms in Java 8 for the problem of random sampling with a reservoir
probsys/optimal-approximate-sampling
Optimal approximate sampling from discrete probability distributions
aakankshaws/numpy-exercise
numpy practice exercise with solution
boonemiller/Ray-Tracer
Ray Tracer implementation in C++, Random Sample AA, multi-threading, bvh acceleration, temporal denoising, soft shadows, and runtime comparisons on different CPUs
zeroboo/nodejs-random-selector
A nodejs module for randomly select elements.
pblischak/zprob
A Zig Module for Random Number Distributions
spatstat/spatstat.core
sub-package of spatstat containing core functionality for data analysis and modelling
org-arl/AlphaStableDistributions.jl
Alpha stable and sub-Gaussian distributions in Julia
Snawoot/terse
Output randomly sampled lines from input stream or file
aneeshnaik/lintsampler
Efficient random sampling via linear interpolation.
jlumbroso/affirmative-sampling
Reference implementation of the Affirmative Sampling algorithm by Jérémie Lumbroso and Conrado Martínez (2022). 🍀
probcomp/TracedRandom.jl
Make Julia code probabilistic-programming-ready by allowing calls to `rand` to be annotated with traced addresses.
acharles7/data-science-notebooks
Credit card fraud detection, gender classification from name etc.
Daniel-Ze/python_scripts
Collection of python scripts
Jangwonjin/valid_cdm
⚡ Validation method of cognitive diagnosis models (CDMs)
Jayplect/credit-risk-classification
In this project, I used a dataset containing the historical lending activity from a peer-to-peer lending services company to build a model that can identify the creditworthiness of borrowers.
ocramz/splitmix-distributions
Sampling procedures for some common random variables based on splitmix
vgherard/gsample
Efficient weighted sampling without replacement in R
amitkp57/dbms-correlated-columns-detection
Detecting correlated columns in DBMS systems using techniques like Pearson Correlation, LSH Minhashing and Random Sampling.
gautamHCSCV/Modelling_Viscoelastic_Objects
This paper proposes an alternative data-driven hap- tic modeling method of homogeneous deformable objects based on a CatBoost approach – a variant of gradient boosting machine learning approach. In this approach, decision trees are trained sequentially to learn the required mapping function for modeling the objects.
jesussantana/Sampling
Perform Data Sampling with Python
kweterings/MonteCarlo_Estimation
An introduction to Monte Carlo methods by estimating π. This code comes in the form of a Python program.
seungwoo-stat/rvMF
Fast Generation of von Mises-Fisher Distributed Pseudo-Random Vectors
smahala02/Monte-Carlo-Simulation
A comprehensive tutorial on Monte Carlo Simulation using Python, demonstrating how random sampling and probabilistic models can be used for various real-world applications, including finance, physics, and engineering.
sprcoder/Customer_Segmentation_ML
A machine learning project to predict Customers/Clients into correct segment to provide promotional information or for product advertising.
lady-bluecopper/NuDHy
Null Models for Directed Hypergraphs
AlexBuccheri/random_sampling
Personal random sampling testing
cicirello/small-sample-experiments
Code and data for experiments for paper "Algorithms for Generating Small Random Samples"
shyammanikandan/Loan_Default_Analysis
Analyze a loan default dataset to understand the factors that contribute to loan defaults.