interpretability-methods

ProphitBet is a Machine Learning Soccer Bet prediction application. It analyzes the form of teams, computes match statistics and predicts the outcomes of a match using advanced Machine Learning (ML) methods. Additionally, it provides betting agents based on Deep Reinforcement Learning (DRL), which can learn optimal betting strategies.

Pytorch implementation of various neural network interpretability methods

Learning clinical-decision rules with interpretable models.

Official code of the CVPR 2022 paper "Proto2Proto: Can you recognize the car, the way I do?"

Experiments with experimental rule-based models to go along with imodels.

Explaining black boxes with a SMILE: Statistical Mode-agnostic Interpretability with Local Explanations

Initial Exploratory Works on Knowledge Tracing in Transformer Based Language Models

CVPR 2021 | Metrics for evaluating interpretability methods.

🦠 DeepDecipher: An open source API to MLP neurons

Code for the paper "Comparing Feature Importance and Rule Extraction for Interpretability on Text Data", XAIE @ ICPR 2022

Metrics for evaluating interpretability methods.

This project focuses on modeling auto encoder-based architectures for unsupervised detection of anomalies in 12-lead electrocardiograms (ECGs)

A repository to study the interpretability of time series networks(LSTM)

Repository for the journal article 'SHAMSUL: Systematic Holistic Analysis to investigate Medical Significance Utilizing Local interpretability methods in deep learning for chest radiography pathology prediction'

A curated list of awesome machine learning interpretability resources.

Research site, private study instruments and evidence registry for observable model behavior. Astro + Cloudflare, with provenance-linked releases.