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Hangzhou He's Projects

gre_prep icon gre_prep

This is a guide for how one can prepare for GRE within a month's duration.

loss-landscapes icon loss-landscapes

Approximating neural network loss landscapes in low-dimensional parameter subspaces for PyTorch

pytorch-grad-cam icon pytorch-grad-cam

Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

pytorch-image-models icon 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

pytorch-loss icon pytorch-loss

label-smooth, amsoftmax, partial-fc, focal-loss, triplet-loss, lovasz-softmax. Maybe useful

pytorch_attribution icon pytorch_attribution

Attribution methods that explain image classification models, implemented in PyTorch, and support batch input and GPU.

riverback.github.io icon riverback.github.io

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

saliency icon saliency

Framework-agnostic implementation for state-of-the-art saliency methods (XRAI, BlurIG, SmoothGrad, and more).

segment-anything icon segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

style2paints icon style2paints

sketch + style = paints :art: (TOG2018/SIGGRAPH2018ASIA)

vit-pytorch icon vit-pytorch

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

xplique icon xplique

👋 Xplique is a Neural Networks Explainability Toolbox

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