In this article, a novel probabilistic MBRL approach, probabilistic neural networks model predictive control (PNMPC) is proposed to tackle this issue. With an iterative learning framework, PNMPC ...

Developed by Meta, PyTorch is a popular machine learning library that helps develop and train neural networks.

AI and AR are transforming industrial IoT by enabling real-time data processing, enhancing operational efficiency, and ...

This paper makes the following contributions: (1) A spiking neural network (SNN) is used to model human decision-making neural circuit from both connectome and functional perspectives. (2) The ...

Elon Musk doesn’t want Tesla to be just an automaker. He wants Tesla to be an AI company, one that’s figured out how to make ...

A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.

Spiking Neural Networks (SNNs) are a pathway that could potentially ... vanishing spikes in BP training and reduce the number of time steps to reduce network latency. In SSTDP, we employ ...

A Hall thruster is a high-efficiency propulsion device using plasma that is used for various difficult space missions, such ...

A research team from KAIST Nuclear and Quantum Engineering presents an AI assesser for Hall-effect ion thrusters, the engines ...

What do you wonder? By The Learning Network A new collection of graphs, maps and charts organized by topic and type from our “What’s Going On in This Graph?” feature. By The Learning ...

The VAE is like a funnel for training the software model to understand less common traffic situations, such as things on the ...

config_frequentist.py: Hyperparameters for main_frequentist file. @article{shridhar2019comprehensive, title={A comprehensive guide to bayesian convolutional neural network with variational inference}, ...