neuro-symbolic-sudoku-solver
DragGAN
| neuro-symbolic-sudoku-solver | DragGAN | |
|---|---|---|
| 1 | 1 | |
| 66 | 88 | |
| - | - | |
| 0.0 | 7.1 | |
| over 2 years ago | 11 months ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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neuro-symbolic-sudoku-solver
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Neuro-Symbolic Sudoku Solver
Github: https://github.com/ashutosh1919/neuro-symbolic-sudoku-solver
DragGAN
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First look at DragGAN - the generative net that allows the user to drag a particular part of an image and shift it to the target place. Try it yourself: https://github.com/.../neural_networks/GAN/draggan.ipynb
Not sure if it's the same one OP used, but looks similar, here's working link: https://github.com/adriaciurana/DragGAN https://colab.research.google.com/github/adriaciurana/DragGAN/blob/master/colab_notebook.ipynb
What are some alternatives?
transformers-interpret - Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.
DragGAN - Official Code for DragGAN (SIGGRAPH 2023)
MAGIST-Algorithm - Multi-Agent Generally Intelligent Simultaneous Training Algorithm for Project Zeta
neural_networks
DiCE - Generate Diverse Counterfactual Explanations for any machine learning model.
News-Sense - A Streamlit app based on Python that fetches top news articles from the News API, generates a summary of each article using the OpenAI GPT-3 model, analyzes the sentiment of the article using the NLTK library, and classifies the article into different categories based on keywords.
sudoku - Can Neural Networks Crack Sudoku?
dnn_from_scratch - A high level deep learning library for Convolutional Neural Networks,GANs and more, made from scratch(numpy/cupy implementation).
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.
BMSG-GAN - [MSG-GAN] Any body can GAN! Highly stable and robust architecture. Requires little to no hyperparameter tuning. Pytorch Implementation
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
deep-RL-trading - playing idealized trading games with deep reinforcement learning