DragGAN VS neuro-symbolic-sudoku-solver

Compare DragGAN vs neuro-symbolic-sudoku-solver and see what are their differences.

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DragGAN neuro-symbolic-sudoku-solver
1 1
89 66
- -
7.1 0.0
12 months ago over 2 years ago
Python Python
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

DragGAN

Posts with mentions or reviews of DragGAN. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-02.

neuro-symbolic-sudoku-solver

Posts with mentions or reviews of neuro-symbolic-sudoku-solver. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing DragGAN and neuro-symbolic-sudoku-solver you can also consider the following projects:

DragGAN - Official Code for DragGAN (SIGGRAPH 2023)

transformers-interpret - Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.

neural_networks

MAGIST-Algorithm - Multi-Agent Generally Intelligent Simultaneous Training Algorithm for Project Zeta

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.

DiCE - Generate Diverse Counterfactual Explanations for any machine learning model.

dnn_from_scratch - A high level deep learning library for Convolutional Neural Networks,GANs and more, made from scratch(numpy/cupy implementation).

sudoku - Can Neural Networks Crack Sudoku?

BMSG-GAN - [MSG-GAN] Any body can GAN! Highly stable and robust architecture. Requires little to no hyperparameter tuning. Pytorch 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.

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