Using Knowledge Elicitation Techniques To Infuse Deep Expertise And Best Practices Into Generative AI

How can we get AI and LLMs to be domain experts? The prior era of AI devised knowledge elicitation techniques. Those are ...

New deep learning model enhances roadside air pollutant forecasting accuracy

A research team led by Prof. Li Xiangxian from the Anhui Institute of Optics and Fine Mechanics, the Hefei Institutes of ...
RealClearPolitics

Andrew Ross Sorkin: We Will Have A Crash, I Just Can't Tell You When Or How Deep

60 MINUTES: Stocks on Wall Street have rallied in recent months, but author Andrew Ross Sorkin sees a crash coming. The question is: when will the bubble pop, and how much will the market slump when ...
Phys.org

Interpretable deep learning network significantly improves tropical cyclone intensity forecast accuracy

Predicting tropical cyclones (TCs) accurately is crucial for disaster mitigation and public safety. Although the forecasting accuracy of TC tracks has improved substantially in recent decades, ...
Scientific Research Publishing

Traffic Speed Prediction Based on Autoencoder and Deep Learning ()

Traffic prediction is the core of intelligent transportation system, and accurate traffic speed prediction is the key to optimize traffic management. Currently, the traffic speed prediction model ...
GitHub

Enhancing EV Cost Prediction Using AutoEncoder-Based Feature Learning

Electric Vehicle (EV) cost prediction involves analyzing complex, high-dimensional data that often contains noise, multicollinearity, and irrelevant features. Traditional regression models struggle to ...
IEEE

Deep Variational Autoencoder Based Parameter Learning of Bayesian Network with Multiple Latent Variables

Abstract: Intelligent systems could be increasingly powerful by applying probabilistic inferences over the dependence relations among observed and latent variables, which could be represented by the ...
Scientific Research Publishing

Shevitski, B., Watkins, Y., Man, N. and Girard, M. (2023) Digital Signal Processing Using Deep Neural Networks: Evaluating the Effectiveness of Hybrid Autoencoder/ Transformer ...

ABSTRACT: The rapid growth of unlabeled time-series data in domains such as wireless communications, radar, biomedical engineering, and the Internet of Things (IoT) has driven advancements in ...
GitHub

Lesson No. 3: Variational autoencoder code for CelebA dataset takes too long to load

train_data = utils.image_dataset_from_directory( "celeba-dataset/img_align_celeba/img_align_celeba", labels = None, color_mode="rgb", image_size = (64, 64), batch ...