Popular GitHub Repositories for Regularization Hyperparameters

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

Open-source implementation of Google Vizier for hyper parameters tuning

A collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.

Training neural models with structured signals.

This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.

Official implementation of "Segment Any Anomaly without Training via Hybrid Prompt Regularization (SAA+)".

The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.

Implementation of DropBlock: A regularization method for convolutional networks in PyTorch.

Tuning hyperparams fast with Hyperband

Implicit Geometric Regularization for Learning Shapes

Simple Implementation of many GAN models with PyTorch.

Keras implementation of the paper "3D MRI brain tumor segmentation using autoencoder regularization" by Myronenko A. (https://arxiv.org/abs/1810.11654).

ML hyperparameters tuning and features selection, using evolutionary algorithms.

[CVPR 2023] DiffusioNeRF: Regularizing Neural Radiance Fields with Denoising Diffusion Models

Library for automatic retraining and continual learning

Official Implementation of Early-Learning Regularization Prevents Memorization of Noisy Labels

A Lightweight Optical Flow CNN - Revisiting Data Fidelity and Regularization, TPAMI 2020

This repo contains the experimentation of the most important deep learning techniques related to Regularization, Optimization and HPO while using LeNet CNN architecture as the playground.

Machine learning algorithms in Dart programming language