A lean C++ library for working with point cloud data
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Updated
Aug 15, 2023 - C++
A lean C++ library for working with point cloud data
torchbearer: A model fitting library for PyTorch
Model manipulation and fitting library based on TensorFlow and optimised for simple and direct manipulation of probability density functions. Its main focus is on scalability, parallelisation and user friendly experience.
piecewise-regression (aka segmented regression) in python. For fitting straight line models to data with one or more breakpoints where the gradient changes.
SourceXtractor++, the next generation SExtractor
JetSeT a framework for self-consistent modeling and fitting of astrophysical relativistic jets
Course Project for the course CS 736
Python framework for multi-parameter optimization and evaluation of protein folding models
Package for fitting/optimization of NeuroML models
This notebook explores the housing dataset from Kaggle to predict Sales Prices of housing using advanced regression techniques such as feature engineering and gradient boosting.
Meta-analysis toolbox for basic research applications. Developed in MATLAB R2016b.
tsiR: An R package for time-series Susceptible-Infected-Recovered models of epidemics
Implementation of the algorithm described in the following paper. Korenberg, M., Billings, S.A. and Liu, Y.P. (1987) An Orthogonal Parameter Estimation Algorithm for Nonlinear Stochastic Systems
Toolbox for change-point detection and ideal-observer analyses of IBL task data
An R package of S3 generic methods for Bayesian analyses that generate MCMC samples
General RANSAC solver with detailed examples.
a gradient-based optimisation routine for highly parameterised non-linear dynamical models
GEARS a toolbox for Global parameter Estimation with Automated Regularisation via Sampling by Jake Alan Pitt and Julio R. Banga
Elegant Mathematica-style model manipulation, fitting and exploration in MATLAB.
Tutorial on Bayesian model fitting with (Py)VBMC.
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