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interpretability-papers

Papers on interpretable deep learning, for review

interpretable-image

Code for "Interpretable Image Recognition with Hierarchical Prototypes"

iternorm-pytorch

This is the pytorch re-implementation of the IterNorm

jackeywang777.github.io

lightcnn

A pytorch implement of "A Light CNN for Deep Face Representation with Noisy Labels"

ml-notes

notes about machine learning

nn_interpretability

Pytorch implementation of various neural network interpretability methods

nndl.github.io

《神经网络与深度学习》 Neural Network and Deep Learning

person-reid-benchmark

A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets

person-reid-triplet-loss-baseline

Rank-1 89% (Single Query) on Market1501 with raw triplet loss, In Defense of the Triplet Loss for Person Re-Identification, using Pytorch

person_reid_baseline_pytorch

Pytorch implement of Person re-identification baseline. We arrived Rank@1=88.24%, mAP=70.68% only with softmax loss. Re-ranking is added.

pointing_game

pretrainedcnnforcub

pretrainedcnnforvoc1

pretrainedcnnforvoc3

project_demo

Demo for Pixel Hop, Pixel Hop++, Interpretable CNN and Face Hop. The most recent version of Saab transform is used in all the projects.

protopformer

ProtoPFormer: Concentrating on Prototypical Parts in Vision Transformers for Interpretable Image Recognition

protopnet

This code package implements the prototypical part network (ProtoPNet) from the paper "This Looks Like That: Deep Learning for Interpretable Image Recognition" (to appear at NeurIPS 2019), by Chaofan Chen* (Duke University), Oscar Li* (Duke University), Chaofan Tao (Duke University), Alina Jade Barnett (Duke University), Jonathan Su (MIT Lincoln Laboratory), and Cynthia Rudin (Duke University) (* denotes equal contribution).

prototree

ProtoTrees: Neural Prototype Trees for Interpretable Fine-grained Image Recognition

pumpkin-book

《机器学习》（西瓜书）公式推导解析，在线阅读地址：https://datawhalechina.github.io/pumpkin-book

python-guide

Python best practices guidebook, written for Humans.

pythonic_ocr

A convolutional neural network implemented in pure numpy.

pytorch-cifar

95.16% on CIFAR10 with PyTorch

pytorch-cnn-visualizations

Pytorch implementation of convolutional neural network visualization techniques

pytorch-gve-lrcn

PyTorch implementations for "Generating Visual Explanations" (GVE) and "Long-term Recurrent Convolutional Networks" (LRCN)

pytorch-image-models

PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more

pytorch-memory-utils

pytorch memory track code

pytorch-playground

Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)

pytorch-receptive-field

Compute CNN receptive field size in pytorch in one line

pytorch-vae

A Collection of Variational Autoencoders (VAE) in PyTorch.