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neuro-symbolic-sudoku-solver
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DiCE | neuro-symbolic-sudoku-solver | |
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2 | 1 | |
1,270 | 66 | |
2.4% | - | |
8.2 | 0.0 | |
11 days ago | over 2 years ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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DiCE
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[D] Have researchers given up on traditional machine learning methods?
- all domains requiring high interpretability absolutely ignore deep learning at all, and put all their research into traditional ML; see e.g. counterfactual examples, important interpretability methods in finance, or rule-based learning, important in medical or law applications
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[R] The Shapley Value in Machine Learning
Counter-factual and recourse-based explanations are alternative approach to model explanations. I used to work in a large financial institution, and we were researching whether counter-factual explanation methods would lead to better reason codes for adverse action notices.
neuro-symbolic-sudoku-solver
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Neuro-Symbolic Sudoku Solver
Github: https://github.com/ashutosh1919/neuro-symbolic-sudoku-solver
What are some alternatives?
OmniXAI - OmniXAI: A Library for eXplainable AI
transformers-interpret - Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.
CARLA - CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
MAGIST-Algorithm - Multi-Agent Generally Intelligent Simultaneous Training Algorithm for Project Zeta
AIX360 - Interpretability and explainability of data and machine learning models
sudoku - Can Neural Networks Crack Sudoku?
interpret - Fit interpretable models. Explain blackbox machine learning.
DragGAN - Unofficial implementation of the DragGAN paper
harakiri - Help applications kill themselves
TicTacToe - Tic Tac Toe game, designed to be used to train a Deep Neural Network via Reinforcement Learning (DQN). It can also be played by 2 humans and features a hard coded AI that never looses and will win if you do not do perfect play against it.
stranger - Chat anonymously with a randomly chosen stranger
Agar.io_Q-Learning_AI - An experiment on the performance of homemade Q-learning AIs in Agar.io depending on their state representation and available actions