The set of CPU/GPU optimised regularisation modules for iterative image reconstruction and other image processing tasks
TOmographic MOdel-BAsed Reconstruction (ToMoBAR) software
In the context of Deep Learning: What is the right way to conduct example weighting? How do you understand loss functions and so-called theorems on them?
A Claude skill for producing compilable LaTeX in computational and applied mathematics — theorems, proofs, algorithms, convergence analyses, numerical experiments and beamer presentations
Python code to fit single-angle dynamic light scattering data using the Tikhonov Philips regularisation
My project to recreate the results in "Understanding Deep Learning Requires Rethinking Generalization"
Mixed Integer Piecewise Regression Algorithm with Regularisation
Horseshoe regression model fitted in PyMC.
Multivariate Polynomial Regression using gradient descent with regularisation
GEARS a toolbox for Global parameter Estimation with Automated Regularisation via Sampling by Jake Alan Pitt and Julio R. Banga
a small machine learning theory practice.
The use case is an application of the regularization technique such as Ridge and Lasso for building a linear regression model for housing price prediction.
Regularisation and Cross-Validation of Determinants of Egalitarian Democracy: Demonstration for R
The goal of this project is to develop and test two text classification systems: Task 1: sentiment analysis, in particular to predict the sentiment of movie review, i.e. positive or negative (binary classification). Task 2: topic classification, to predict whether a news article is about International issues, Sports or Business (multiclass class…
In this project we will build multiple CNN models for CIFAR-10 Image Classification
Repo for machine learning classes
Predicting whether two persons meeting in a speed dating event get matched using L2 regularised simple neural network with 90% accuracy.
Jacobian regularisation for neural networks (PyTorch) and hyperparameter tuning with Skorch
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