#
sampling-methods
Here are 92 public repositories matching this topic...
Research on sampling methods for real-time volume rendering
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Aug 13, 2017 - GLSL
a framework for training sequence-level deep learning networks
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Jul 21, 2020 - Jupyter Notebook
Collection of Monte Carlo (MC) and Markov Chain Monte Carlo (MCMC) algorithms applied on simple examples.
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Dec 20, 2017 - Python
Python toolbox for sampling Determinantal Point Processes
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May 22, 2020 - Jupyter Notebook
MCMC sample analysis, kernel densities, plotting, and GUI
statistical-inference
mcmc
kernel-density-estimation
sampling-methods
contour-plot
plotting-in-python
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Jul 7, 2020 - Python
Public version of PolyChord: See polychord.co.uk for PolyChordPro
statistics
astronomy
mpi
gfortran
cosmology
bayesian-inference
particle-physics
openmpi
nested-sampling
posterior
log-likelihood
sampling-methods
polychord
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Aug 11, 2020 - Fortran
Uni{corn|form} toolkit
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Apr 14, 2020 - C++
Can we predict accurately on the skewed data? What are the sampling techniques that can be used. Which models/techniques can be used in this scenario? Find the answers in this code pattern!
machine-learning
data-mining
analytics
machine-learning-algorithms
data-visualization
datascience
data-analysis
fraud-prevention
fraud-detection
fraud
sampling-methods
skewness
skew-correction
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Jul 7, 2020 - Jupyter Notebook
python
machine-learning
inference
sampling
bayesian-inference
general-purpose
mcmc
mcmc-sampler
sampling-methods
probabilistic-data-analysis
black-box-bayesian-inference
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Aug 3, 2020 - Python
Library for producing and processing on the Adaptive Particle Representation (APR).
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Aug 16, 2020 - C++
Piecewise Deterministic Sampler library (Bouncy particle sampler, Zig Zag sampler, ...)
graphical-models
bayesian-inference
markov-chain-monte-carlo
sampling-methods
zig-zag-sampler
bouncy-particle-sampler
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Oct 25, 2018 - Julia
AAAI & CVPR 2016: Preconditioned Stochastic Gradient Langevin Dynamics (pSGLD)
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Sep 16, 2018 - MATLAB
The Fast Loaded Dice Roller: A Near-Optimal Exact Sampler for Discrete Probability Distributions
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Jun 27, 2020 - Python
Python package for learning the graphical structure of Bayesian networks, parameter learning, inference and sampling methods.
bayesian-inference
dag
structure-learning
sampling-methods
directed-acyclic-graph
parameter-learning
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Jun 29, 2020 - Python
RRT Star path planning for dynamic obstacle avoidance for the F110 Autonomous Car
cpp
rrt
ros
rrt-star
kinetic
sampling-methods
dynamic-obstacles
melodic
pathplanning
racecar-simulator
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Nov 14, 2019 - C++
AISTATS 2019: Reference-based Adversarial Sampling & Its applications to Soft Q-learning
reinforcement-learning
adversarial-learning
sampling-methods
entropy-regularizer
amortized-inference
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Jan 21, 2019 - Jupyter Notebook
Anamoly Detection for Detecting Defected Manufactured Semi-Conductors, as in this case of Classification, the Defected Chips would be very less in comparison to perfect Chips so we have apply either Over-Sampling or Under-Sampling.
machine-learning
data-visualization
feature-extraction
classification
outlier-detection
sampling-methods
precision-recall-curve
anamoly-detection
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May 20, 2019 - Jupyter Notebook
"Progressive Multi-Jittered Sample Sequences" in C++
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Jul 31, 2020 - Jupyter Notebook
Samplers to obtain pointclouds from CAD meshes
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Jul 9, 2020 - C++
Microsynthesis using quasirandom sampling and/or IPF
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Aug 5, 2020 - C++
This repository provides code for SVD and Importance sampling-based algorithms for large scale topic modeling.
linear-algebra
topic-modeling
unsupervised-learning
svd
sampling-methods
spectral-clustering
randomized-algorithm
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Mar 22, 2019 - C++
PyTorch implementation for " Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference" (https://arxiv.org/abs/1810.02555).
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Dec 29, 2018 - Python
Plot, edit, generate and analysis neuron morphologies! and a lot more...
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Feb 11, 2020 - Jupyter Notebook
Experimental code: adaptive importance sampling for bayesian networks. -- I think I may have broken this code.
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Jun 8, 2019 - Python
A basic binary classification class that uses sampling techniques in order to deal with rare events (e.g. 10% or less).
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Aug 30, 2018 - Python
Subsampled Riemannian trust-region (RTR) algorithms
big-data
optimization
optimization-algorithms
gradient-descent-algorithm
stochastic-optimizers
stochastic-gradient-descent
sampling-methods
subsample
large-scale-optimizations
riemannian-geometry
riemannian-manifold
trust-region
sub-sampling
second-order-optimization
riemannian-optimization
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Jun 20, 2019 - MATLAB
Some methods to sampling data points from a given distribution.
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Jul 16, 2018 - Python
Tools for efficient global sensitivity analyses for models with correlated input parameters.
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Jun 3, 2020 - Python
Thermostat-assisted continuously-tempered Hamiltonian Monte Carlo for Bayesian learning
deep-learning
bayesian-methods
hybrid-monte-carlo
bayesian-nonparametric-models
bayesian-neural-networks
sampling-methods
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Dec 10, 2018 - Python
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The caustics texture is currently being sampled without taking flow into account. This could be something worth playing aroud with and seeing if we could get good results.
A good place to look would be how flow affects the sampling of the foam texture in the Ocean Shader.