david-mys Goto Github PK

annomachine

autonomous-car-dataset-project

bert4rec

BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer

bigfive-web

Website for taking personality tests

bracelet

Do you remember those star wars ewoks movies? This is the device the Towani Family were wearing in those movies, showing their lifesigns.

caml

cnn

cnn

compare_gan

Compare GAN code.

contextual2static

All materials that accompany/are needed to reproduce ACL 2020 paper - Interpreting Pretrained Contextualized Representations via Reductions to Static Embeddings

dissect

Code for the Proceedings of the National Academy of Sciences 2020 article, "Understanding the Role of Individual Units in a Deep Neural Network"

django-docker-compose-deployment

dsb2019

https://www.kaggle.com/c/data-science-bowl-2019

fpga

hui

gandissect

Pytorch-based tools for visualizing and understanding the neurons of a GAN. https://gandissect.csail.mit.edu/

home

Fashionpedia project website

icnn

A pytorch implementation of interpretable convolutional neural network.

interpretablecnn

jalammar.github.io

Build a Jekyll blog in minutes, without touching the command line.

mask_rcnn

mask_rcnn21

ml-react-app-template

This is a template for creating a Machine Learning application with its front-end developed using React which interacts with a Flask service as the back-end and makes predictions.

mmbt

Supervised Multimodal Bitransformers for Classifying Images and Text

mturk

multimodalexplanations

Code release for Park et al. Multimodal Multimodal Explanations: Justifying Decisions and Pointing to the Evidence. in CVPR, 2018

netdissect

Network Dissection http://netdissect.csail.mit.edu for quantifying interpretability of deep CNNs.

netdissect-lite

Light version of Network Dissection for Quantifying Interpretability of Networks

pog

the datasets of the paper POG

posenorm_fewshot

(CVPR2020) Revisiting Pose-Normalization for Fine-Grained Few-Shot Recognition

progressive_growing_of_gans

Progressive Growing of GANs for Improved Quality, Stability, and Variation

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).