IEEE

AI-Driven Energy Optimization: Household Power Consumption Prediction With LSTM Networks ...

Abstract: Energy optimization is critical in smart home systems and IoT networks, necessitating innovative models that reduce energy use. This research presents two Long Short-Term Memory (LSTM) ...
Scientific Research Publishing

Gold Price Prediction Based on LSTM-Attention Combined Model ()

This paper explores effective methods for predicting gold prices, proposing three modeling strategies: a standalone Long Short-Term Memory (LSTM) network, a Convolutional Self-Attention (CSA) Network, ...
Digi Times

Google reportedly launches TorchTPU project to boost TPU compatibility with PyTorch

Google has reportedly initiated the TorchTPU project to enhance support for the PyTorch machine learning framework on its tensor processing units (TPUs), aiming to challenge the software dominance of ...
来自MSN

Network in Network (NiN) Explained – Deep Neural Network Tutorial with PyTorch

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...
GitHub

基于pytorch搭建多特征LSTM时间序列预测（附完整代码）.md

对于LSTM神经网络的概念想必大家也是熟练掌握了，所以本文章不涉及对LSTM概念的解读，仅解释如何使用**pytorch**使用LSTM进行时间序列预测，复原使用代码实现的全流程。 ## 数据获取与预处理 首先预览一下本次实验使用的数据集，该数据集共有三个特征，将最后 ...
Frontiers

Developing an explainable deep learning module based on the LSTM framework for flood prediction

Long short-term memory (LSTM) networks have become indispensable tools in hydrological modeling due to their ability to capture long-term dependencies, handle non-linear relationships, and integrate ...
Game Rant

Most Iconic Tutorials In Games, Ranked

Robbie has been an avid gamer for well over 20 years. During that time, he's watched countless franchises rise and fall. He's a big RPG fan but dabbles in a little bit of everything. Writing about ...