This project shows how to find anomalies in financial time series data, specifically the stock values of Apple (AAPL), using a LSTM Autoencoder. Stock price anomalies may be a sign of major market ...
CUDA_VISIBLE_DEVICES=0 python scripts/sample.py -d kitti -r models/lidm/kitti/[model_name]/model.ckpt -n 2000 --eval Besides, to train your own LiDAR Diffusion Models ...
Unsupervised domain adaptation has provoked vast amount of attention and research in past decades. Among all the deep-based methods, the autoencoder-based approach have achieved sound performance for ...
Abstract: Lithofacies classification is an indispensable procedure in well logging and seismic data interpretation. We propose a novel deep classified autoencoder learning approach to identify ...
Abstract: Modern energy systems often regarded as smart grid (SG) systems are cyber-physical systems (CPS) equipped with advanced metering and smart sensing devices, leading to a high-dimensional data ...
A Leap Forward in Computer Vision: Facebook AI Says Masked Autoencoders Are Scalable Vision Learners
The paper Masked Autoencoders Are Scalable Vision Learners, published this week by Kai-Ming He, Xinlei Chen and their Facebook AI Research (FAIR) team, has become a hot topic in the computer vision ...
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