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 ...
IEEE

AI-Driven Energy Optimization: Household Power Consumption Prediction With LSTM Networks and PyTorch-Ray Tune in Smart IoT Systems

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) ...
Frontiers

Velocity-aware spatial-temporal attention LSTM model for inverse dynamic model learning of manipulators

Institute of Robotics and Intelligent Systems, Wuhan University of Science and Technology, Wuhan, Hubei, China Introduction: An accurate inverse dynamics model of manipulators can be effectively ...
GitHub

Backward step of derivative LSTM

LSTM seem not support some derivative manipulation for the training part with the new version of pytorch. When the output of a LSTM layer is used with some derivation manipulation (eg torch.autograd, ...
InfoWorld

TensorFlow, PyTorch, and JAX: Choosing a deep learning framework

Deep learning is changing our lives in small and large ways every day. Whether it’s Siri or Alexa following our voice commands, the real-time translation apps on our phones, or the computer vision ...
syncedreview

LSTM Is Back! A Deep Implementation of the Decades-old Architecture Challenges ViTs on Long Sequence Modelling

In less than two years since their introduction, vision transformers (ViT) have revolutionized the computer vision field, leveraging transformer architectures’ powerful self-attention mechanisms to ...
Visual Studio Magazine

Sentiment Classification of IMDB Movie Review Data Using a PyTorch LSTM Network

This demo from Dr. James McCaffrey of Microsoft Research of creating a prediction system for IMDB data using an LSTM network can be a guide to create a classification system for most types of text ...
GitHub

Import ONNX LSTM converted from PyTorch

I am trying to import a simple LSTM network converted from Pytorch to ONNX. The model imports and executes perfectly in both PyTorch and ONNX. When I try to import in ...
marktechpost

Implementing Batching for Seq2Seq Models in Pytorch

In this tutorial, we will discuss how to implement the batching in sequence2sequene models using Pytorch. We will implement batching by building a Recurrent Neural Network to classify the nationality ...
marktechpost

Classifying the Name Nationality of a Person using LSTM and Pytorch

The personal name tends to have different variations from country to country or even within a country. Typically the name of a person can be broken into two halves. The first name is the name given at ...