Beyond Straight-Through

👋 Puncc is a python library for predictive uncertainty quantification using conformal prediction.

Federated Learning (FL) experiment simulation in Python.

Rule Induction Partitioning Estimator

Reuse your features: unifying retrieval and feature-metric alignment (ICRA 2023)

DeepTables: Deep-learning Toolkit for Tabular data

The code of NeurIPS 2021 paper "Scalable Rule-Based Representation Learning for Interpretable Classification" and TPAMI paper "Learning Interpretable Rules for Scalable Data Representation and Clas…

Rule Extraction Methods for Interactive eXplainability

A python implementation of C4.5 algorithm by R. Quinlan

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

A Python library for explainable AI using approximate reasoning

repository for R library "sbrlmod"

Python Interface of the Scalable Bayesian Rule Lists

NSGA2, NSGA3, R-NSGA3, MOEAD, Genetic Algorithms (GA), Differential Evolution (DE), CMAES, PSO

Dynamic feature selection based on conditional mutual information

Lightweight, useful implementation of conformal prediction on real data.

Code for the paper "Estimating Conditional Mutual Information for Dynamic Feature Selection"

A game theoretic approach to explain the output of any machine learning model.

A simple and elegant Jekyll theme for an academic personal homepage

ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any model or data and different Shapley Values for tree-based m…

ADE20K Dataset

Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm

Robust fine-tuning of zero-shot models

Awesome list for research on CLIP (Contrastive Language-Image Pre-Training).

Faster RCNN model in Pytorch version, pretrained on the Visual Genome with ResNet 101

Artemis Speaker Tools B

Learning to ground explanations of affect for visual art.

[CVPR 2016] Unsupervised Feature Learning by Image Inpainting using GANs

The universal visitation law of human mobility (Nature)

Code for the paper: It is Okay to Not Be Okay: Overcoming Emotional Bias in Affective Image Captioning by Contrastive Data Collection