This project classifies smoking images using VGG19 with data augmentation, and Captum for model explainability, identifying key features per prediction.

Interpretability Metrics

COVID-19 forecasting model for East Java cities using Joint Learning. My undergrad thesis.

Based on the papers "Interpretability Beyond Feature Attribution: QuantitativeTestingwithConceptActivationVectors(TCAV)" and Captum's instantiation https://captum.ai/docs/captum_insights, we developed this frontend for the Captum project based on the streamlit framework.

Collection of associated files for my bachelor thesis

Deep_classiflie_db is the backend data system for managing Deep Classiflie metadata, analyzing Deep Classiflie intermediate datasets and orchestrating Deep Classiflie model training pipelines. Deep_classiflie_db includes data scraping modules for the initial model data sources. Deep Classiflie depends upon deep_classiflie_db for much of its anal…

"XAI를 위한 Attribution Method 접근법 분석 및 동향 Analysis and Trend of Attribution Methods for XAI" 에서 사용한 코드와 예시를 공개

Model interpretability for Explainable Artificial Intelligence

PyTorch Beginner Workshop (Brad Heintz)

Deep Classiflie is a framework for developing ML models that bolster fact-checking efficiency. As a POC, the initial alpha release of Deep Classiflie generates/analyzes a model that continuously classifies a single individual's statements (Donald Trump) using a single ground truth labeling source (The Washington Post). For statements the model d…

OdoriFy is an open-source tool with multiple prediction engines. This is the source code of the webserver.

Interpretable graph classifications using Graph Convolutional Neural Network

XAI-Tris

This repository contains the source code for Indoor Scene Detector, a full stack deep learning computer vision application.

End-to-end toxic Russian comment classification

We introduce XBrainLab, an open-source user-friendly software, for accelerated interpretation of neural patterns from EEG data based on cutting-edge computational approach.

Cyber Security AI Dashboard

Training a CNN to recognize the current Go position with photorealistic renders

Trained Neural Networks (LSTM, HybridCNN/LSTM, PyramidCNN, Transformers, etc.) & comparison for the task of Hate Speech Detection on the OLID Dataset (Tweets).