This an implementation adapted from Rachnog Neural networks for algorithmic trading. Part One — Simple time series forecasting and this code. This uses Keras library LSTM module to predict stock return prices form S&P 500 index price movements. You can modify this model to acheive better results.
3D-Transformer: Molecular Representation with Transformer in 3D Space
Deep API Deep Learning as Cloud APIs. This project provides pre-trained deep learning models as a cloud API service. A web interface is available as w
Raster Perspective Apply a perspective transformation to bitmap image using the selected path as envelope, without the need to use an external softwar
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GULAG: GUessing LAnGuages with neural networks Classify languages in text via neural networks. Привет! My name is Egor. Was für ein herrliches Frühl
PyImpetus PyImpetus is a Markov Blanket based feature selection algorithm that selects a subset of features by considering their performance both indi
The dual numbers can do efficient autodiff! The codual numbers are a simple meth
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Semantically Contrastive Learning for Low-light Image Enhancement Here, we propose an effective semantically contrastive learning paradigm for Low-lig
HandGestureDetection This program uses a Haar Cascade algorithm to detect the presence of your hand, and then passes it on to a self-created and self-
Introduction YOLOX is an anchor-free version of YOLO, with a simpler design but better performance! It aims to bridge the gap between research and ind
SSUL - Official Pytorch Implementation (NeurIPS 2021) SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning Sun
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Self-Calibrating Neural Radiance Fields, ICCV, 2021 Project Page | Paper | Video Author Information Yoonwoo Jeong [Google Scholar] Seokjun Ahn [Google
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