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google-research

Google Research

implicit-regularization-resnets-nodes

Implicit Regularization of ResNets towards Neural ODEs

jacobian_free_backprop

Implicit networks can be trained efficiently and simply by using Jacobian-free Backprop (JFB).

jaxopt

Hardware accelerated, batchable and differentiable optimizers in JAX.

lipestimation

local-lipschitz-constants

[NeurIPS 2022] Code for paper "Efficiently Computing Local Lipschitz Constants of Neural Networks via Bound Propagation"

mamba-minimal

Simple, minimal implementation of the Mamba SSM in one file of PyTorch.

michaelsdr.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

mistral-src

Reference implementation of Mistral AI 7B v0.1 model.

momentumnet

Drop-in replacement for any ResNet with a significantly reduced memory footprint and better representation capabilities

pytorch-image-models

PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNet-V3/V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

resnet_nodes

Do ResNets discretize Neural ODEs?

sinkformers

Transformers with doubly stochastic attention

t2t-vit

ICCV2021, Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet

vit-cifar

PyTorch implementation for Vision Transformer[Dosovitskiy, A.(ICLR'21)] modified to obtain over 90% accuracy FROM SCRATCH on CIFAR-10 with small number of parameters (= 6.3M, originally ViT-B has 86M).