autoregressive
Papers-in-100-Lines-of-Code
| autoregressive | Papers-in-100-Lines-of-Code | |
|---|---|---|
| 1 | 3 | |
| 66 | 582 | |
| - | - | |
| 4.4 | 5.4 | |
| about 2 years ago | 4 days ago | |
| Python | Python | |
| MIT License | MIT License |
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.
autoregressive
Papers-in-100-Lines-of-Code
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How do I run this code from Papers in 100 lines of code?
I wanted to try the some code written by Maxime Vandegar https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/KiloNeRF_Speeding_up_Neural_Radiance_Fields_with_Thousands_of_Tiny_MLPs
- [P] Implementation of research papers (GANs, VAEs, 3d reconstruction, ...) in 100 lines of PyTorch code
- [P] Papers-in-100-Lines-of-Code: Implementation of research papers (GANs, VAEs, Meta-learning, 3d reconstruction, ...) in 100 lines of PyTorch code.
What are some alternatives?
denoising-diffusion-pytorch - Implementation of Denoising Diffusion Probabilistic Model in Pytorch
EasyOCR - Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
awesome-normalizing-flows - Awesome resources on normalizing flows.
taichi-ngp-renderer - An Instants-NGP renderer that has been implemented using Taichi
pytorch-lightning - Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning]
CelebV-HQ - [ECCV 2022] CelebV-HQ: A Large-Scale Video Facial Attributes Dataset
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
rtdl-num-embeddings - (NeurIPS 2022) On Embeddings for Numerical Features in Tabular Deep Learning
nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
artbench - Benchmarking Generative Models with Artworks
MTR - The official implementation of the paper "Rethinking Data Augmentation for Tabular Data in Deep Learning"