A collection of learning resources for curious software engineers
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Updated
Sep 16, 2024 - Python
A collection of learning resources for curious software engineers
Learn OpenCV in 4 Hours - Code used in my Python and OpenCV course on freeCodeCamp.
Concept Bottleneck Models, ICML 2020
Modern port of Melanie Mitchell's and Douglas Hofstadter's Copycat
Meaningfully debugging model mistakes with conceptual counterfactual explanations. ICML 2022
Code for the paper "Post-hoc Concept Bottleneck Models". Spotlight @ ICLR 2023
PIP-Net: Patch-based Intuitive Prototypes Network for Interpretable Image Classification (CVPR 2023)
Repository for our NeurIPS 2022 paper "Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off" and our NeurIPS 2023 paper "Learning to Receive Help: Intervention-Aware Concept Embedding Models"
A complementary resource that helps python programmers to learn Haskell
Agorithms and data structures in Python 🐍
This project's aim is to provide a sample of my abilities in the form of a challange. The challange is to provide a solution to all exercises in the book Computational Physics by Mark Newman
Codebase for Neuro-Symbolic Continual Learning.
A 11 week workshop for Data Structure concepts and Algorithms.
Codebase for the paper: Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts
Official implementation of MICCAI2024 paper "Evidential Concept Embedding Models: Towards Reliable Concept Explanations for Skin Disease Diagnosis"
Software Testing Techniques course offered at Kansas State University in Spring'16 and Spring'17
Concept Relevance Propagation for Localization Models, accepted at SAIAD workshop at CVPR 2023.
This repository contains most of the Important codes I've learned so far and some Important concepts. I Contribute Solutions to problems every day.
Concept bottleneck models for multiview data with incomplete concept sets
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