neozot-py
tabnet
| neozot-py | tabnet | |
|---|---|---|
| 1 | 8 | |
| 7 | 2,482 | |
| - | 0.8% | |
| 10.0 | 4.8 | |
| over 1 year ago | 3 months 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.
neozot-py
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Arxiv articles suggestions based on your Zotero library
I have recently released a Zotero addon to suggest items from arxiv based on your zotero library. It is available at https://github.com/v-i-s-h/neozot-py and also via pip (pip install neozot). Please refer to README.md (https://github.com/v-i-s-h/neozot-py/blob/main/README.md) for usage.
tabnet
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Time series data into a CNN
There's architectures that operate on tabular data from a few years back now that uses CNN's and self attention. .look at tabnet for inspiration: https://github.com/dreamquark-ai/tabnet
- [P] Stable Diffusion in Tensorflow / Keras
- [D] Opinions about TabNet
- Deep Learning Models to do Regression on a Tabular Data
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Tried so many different models but cant get good accuracy
I tried some other projects like [tabnet](https://github.com/dreamquark-ai/tabnet) they are also yielding *decent* results, but not more than 0.64.
- [P] pytorch-widedeep v1.0.9: the Perceiver and the FastFormer for tabular data are now available in the library
- [D] Why Neural Networks for tabular data are bad?
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Feature Importance in Multiclass problems
Are you solving a tabular problem? If it is so, you can use TabNet to plot them. It also supports multiclass and multilabel.
What are some alternatives?
notion-scholar - Reference management solution using Python and Notion.
tab-transformer-pytorch - Implementation of TabTransformer, attention network for tabular data, in Pytorch
dl-4-tsc - Deep Learning for Time Series Classification
pytorch-widedeep - A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch
easy-entrez - Retrieve PubMed articles, text-mining annotations, or molecular data from >35 Entrez databases via easy to use Python package - built on top of Entrez E-utilities API.
autogluon - Fast and Accurate ML in 3 Lines of Code
summarizepaper - An AI-powered arXiv paper summarization website with a virtual assistant for answering questions.
Linear-Multihead-Attention - Reproducing the Linear Multihead Attention introduced in Linformer paper (Linformer: Self-Attention with Linear Complexity)
Super-SloMo - PyTorch implementation of Super SloMo by Jiang et al.
ExtractTable-py - Python library to extract tabular data from images and scanned PDFs
torchsde - Differentiable SDE solvers with GPU support and efficient sensitivity analysis.
rtdl - Research on Tabular Deep Learning (Python package & papers) [Moved to: https://github.com/Yura52/rtdl]