Popular GitHub Repositories for Dropout Rates

Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学

Fine-tuned MARL algorithms on SMAC (100% win rates on most scenarios)

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

Pax is a Jax-based machine learning framework for training large scale models. Pax allows for advanced and fully configurable experimentation and parallelization, and has demonstrated industry leading model flop utilization rates.

Code for Adam-mini: Use Fewer Learning Rates To Gain More https://arxiv.org/abs/2406.16793

Deep learning library in plain Numpy.

Multi-hop knowledge graph reasoning learned via policy gradient with reward shaping and action dropout

:microscope: Nano size Theano LSTM module

Artificial Intelligence Learning Notes.

MorphL Community Edition uses big data and machine learning to predict user behaviors in digital products and services with the end goal of increasing KPIs (click-through rates, conversion rates, etc.) through personalization

MNIST classification using Convolutional NeuralNetwork. Various techniques such as data augmentation, dropout, batchnormalization, etc are implemented.

Extensive acceptance rates and information of main AI conferences

PyTorch implementations of LSTM Variants (Dropout + Layer Norm)

A Deep Learning and preprocessing framework in Rust with support for CPU and GPU.

[TPAMI 2022] "Bag of Tricks for Training Deeper Graph Neural Networks A Comprehensive Benchmark Study" by Tianlong Chen*, Kaixiong Zhou*, Keyu Duan, Wenqing Zheng, Peihao Wang, Xia Hu, Zhangyang Wang

My workshop on machine learning using python language to implement different algorithms

BabyGPT: Build Your Own GPT Large Language Model from Scratch Pre-Training Generative Transformer Models: Building GPT from Scratch with a Step-by-Step Guide to Generative AI in PyTorch and Python

Bayesian Neural Network in PyTorch

PyTorch Implementations of Dropout Variants

Pytorch implementation of Variational Dropout Sparsifies Deep Neural Networks