model-fitting

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.

SourceXtractor++, the next generation SExtractor

Python framework for multi-parameter optimization and evaluation of protein folding models

JetSeT a framework for self-consistent modeling and fitting of astrophysical relativistic jets

tsiR: An R package for time-series Susceptible-Infected-Recovered models of epidemics

An R package of S3 generic methods for Bayesian analyses that generate MCMC samples

Meta-analysis toolbox for basic research applications. Developed in MATLAB R2016b.

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

Course Project for the course CS 736

Elegant Mathematica-style model manipulation, fitting and exploration in MATLAB.

GEARS a toolbox for Global parameter Estimation with Automated Regularisation via Sampling by Jake Alan Pitt and Julio R. Banga

HVAC model fitting tool from measured data, basic tkinter gui

Investigated factors that affect the likelihood of charity donations being made based on real census data. Developed a naive classifier to compare testing results to. Trained and tested several supervised machine learning models on preprocessed census data to predict the likelihood of donations. Selected the best model based on accuracy, a modified F-scoring metric, and algorithm efficiency.

a curvature descent optimisation routine for highly parameterised non-linear dynamical models

General RANSAC solver with detailed examples.

Johns Hopkins University Bloomberg School of Public Health: Data Science Specialization Program: Regression Models Course: Motor Trend Project repo: date created 61229

This MATLAB script fits either a linear or hyperbolic function to time-series data (e.g., growth data).

Visualization and model fitting for Kobe Bryant shots over the course of his career.

EDA, visualization and model fitting of time series data for the Store Item Demand Forecasting Kaggle competition using the Prophet package. The goal of the competition is to predict the sales of 50 different items at 10 different stores over 3 months. Results would be in the 57th percentile.

Finding Donors for CharityML

code to infer model parameters from data (first dedicated to the dynamic clicks task)

Statistical Modelling of Swine Flu Outbreak Data

Fitting a stochastic individual based model for arboviral disease.

The projects which involve the use of ML concepts

Semester Project for Timeseries Course / Aristotle University of Thessaloniki / Winter Semester 2020

Reference repository for code used in our NBDT publication on the dynamic clicks task

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.