residual-connections

There are 0 repository under residual-connections topic.

ytchx1999 / PyG-OGB-Tricks
Bags of Tricks in OGB (node classification) with GCNs.
ogb graph-neural-networks graph-convolutional-networks open-graph-benchmark node-classification residual-connections gnns torch-geometric
Language:Python 34
BabyGPT-Build_GPT_From_Scratch
TatevKaren / BabyGPT-Build_GPT_From_Scratch
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
attention-is-all-you-need dropout-layers gpt gpt-3 large-language-models layer-normalization llm-training llms multi-head-self-attention neural-networks python pytorch residual-connections transformers
Language:Python 31
paulpuren / PhyCRNet
Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs
partial-differential-equations physics-informed-learning encoder-decoder-architecture autoregressive residual-connections convlstm simulation
Language:Python 17
athanatos96 / CNN-and-Residual-Connections-for-Cow-Teat-Image-Classification
Paper Name: Convolutional Neural Networks and Residual Connections for Cow Teat Image Classification. Testing the impact of Convolutional Neural layers and Residual Conections in the accuracy of dairy Cows Teat Imaga classification Dataset from and testing software: https://github.com/YoushanZhang/SCTL
artificial-intelligence machine-learning convolutional-neural-networks image-classification pytorch residual-connections residual-networks
Language:Jupyter Notebook 1
hwixley / MLP-coursework2
Machine Learning Practical - Coursework 2: Analysing problems with the VGG deep neural network architectures (with 8 and 38 hidden layers) on the CIFAR100 dataset by monitoring gradient flow during training. And exploring solutions using batch normalization and residual connections.
cifar100 convolutional-neural-networks exploding-gradient vanishing-gradient batch-normalization residual-connections vgg
Language:Python
hwixley / MLP-coursework2-report
Machine Learning Practical - Coursework 2 Report: Analysing problems with the VGG deep neural network architectures (with 8 and 38 hidden layers) on the CIFAR100 dataset by monitoring gradient flow during training. And exploring solutions using batch normalization and residual connections.
batch-normalization cifar100 convolutional-neural-networks exploding-gradient residual-connections vanishing-gradient vgg
Language:TeX

residual-connections

ytchx1999 / PyG-OGB-Tricks

TatevKaren / BabyGPT-Build_GPT_From_Scratch

paulpuren / PhyCRNet

athanatos96 / CNN-and-Residual-Connections-for-Cow-Teat-Image-Classification

hwixley / MLP-coursework2

hwixley / MLP-coursework2-report