mahdavinejad Goto Github PK

best-readme-template

An awesome README template to jumpstart your projects!

data.ai

How to manage our data.

docker-hadoop

Apache Hadoop docker image

ecg2rr

ECG to RR

efficient-capsnet

Official TensorFlow code for the paper "Efficient-CapsNet: Capsule Network with Self-Attention Routing".

hierarchical-attention-network-

Hierarchical Attention Network for Explainable Depression Detection on Twitter

hierarchicalprototypes

Code for "Interpretable Image Recognition with Hierarchical Prototypes"

imagenet-datasets-downloader

ImageNet dataset downloader. Creates a custom dataset by specifying the required number of classes and images in a class.

imagenetloader.torch

some old code that i wrote, might be useful to others

imagequality

Image Quality Evaluator

label-free-cbm

A new framework to transform any neural networks into an interpretable concept-bottleneck-model (CBM) without needing labeled concept data

letter-recognition

A test Repository for all people in world

mentalllama

This repository introduces MentaLLaMA, the first open-source instruction following large language model for interpretable mental health analysis.

mmbt

Supervised Multimodal Bitransformers for Classifying Images and Text

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, published at CVPR2021

recommender

seahawk

sentiment

social-media-depression-detector

:pensive: :disappointed: :persevere: :confounded: :weary: Detect depression on social media using the ssToT method introduced in our ASONAM 2017 paper titled "Semi-Supervised Approach to Monitoring Clinical Depressive Symptoms in Social Media"