LSTM Model

Long Short-Term Memory (LSTM) networks are a type of recurrent neural network designed to effectively process sequential data by addressing the vanishing gradient problem, enabling them to learn long-term dependencies. Current research focuses on applying LSTMs to diverse prediction tasks, including financial markets, environmental modeling, healthcare diagnostics, and natural language processing, often in hybrid architectures combining LSTMs with convolutional neural networks or transformers to improve accuracy and robustness. The widespread applicability of LSTMs across various domains highlights their significance in advancing machine learning capabilities and their potential for impactful real-world applications.

Papers

December 28, 2023

Predicting Parkinson's disease evolution using deep learning
Maria Frasca, Davide La Torre, Gabriella Pravettoni, Ilaria Cutica
Deep Learning Parkinson Disease LSTM Model Parkinson'S Disease Disease Progression

November 17, 2023

Hashing it Out: Predicting Unhealthy Conversations on Twitter
Steven Leung, Filippos Papapolyzos
Social Medium Twitter Resource LSTM Model Twitter Corpus

November 3, 2023

RigLSTM: Recurrent Independent Grid LSTM for Generalizable Sequence Learning
Ziyu Wang, Wenhao Jiang, Zixuan Zhang, Wei Tang, Junchi Yan
Sequential Model LSTM Model Standard LSTM

August 18, 2023

ICU Mortality Prediction Using Long Short-Term Memory Networks
Manel Mili, Asma Kerkeni, Asma Ben Abdallah, Mohamed Hedi Bedoui
Long Short Term Memory LSTM Model Data Analysis Intensive Care Unit Mortality

July 14, 2023

Long Short-term Memory with Two-Compartment Spiking Neuron
Shimin Zhang, Qu Yang, Chenxiang Ma, Jibin Wu, Haizhou Li, Kay Chen Tan
Long Short Term Memory Neuromorphic Computing Neuron Model LSTM Model Spiking Neuron Leaky Integrate and Fire Neuron

June 21, 2023

SIFTER: A Task-specific Alignment Strategy for Enhancing Sentence Embeddings
Chao Yu, Wenhao Zhu, Chaoming Liu, Xiaoyu Zhang, Qiuhong zhai
Pre Trained Model Sentiment Analysis Sentence Embeddings Natural Language Processing Task LSTM Model Task Alignment Bio Sieve

June 5, 2023

Interval Load Forecasting for Individual Households in the Presence of Electric Vehicle Charging
Raiden Skala, Mohamed Ahmed T. A. Elgalhud, Katarina Grolinger, Syed Mir
Long Short Term Memory Speech Presence Load Forecasting LSTM Model Electric Vehicle Charging Interval Prediction Residential Household

May 8, 2023

A LSTM and Cost-Sensitive Learning-Based Real-Time Warning for Civil Aviation Over-limit
Yiming Bian
LSTM Network LSTM Model

April 25, 2023

LSTM-based Load Forecasting Robustness Against Noise Injection Attack in Microgrid
Amirhossein Nazeri, Pierluigi Pisu
LSTM Network Load Forecasting LSTM Model DC Microgrid Application Black Box Adversarial Attack Load Prediction

April 6, 2023

Deep Long-Short Term Memory networks: Stability properties and Experimental validation
Fabio Bonassi, Alessio La Bella, Giulio Panzani, Marcello Farina, Riccardo Scattolini
Long Short Term Memory Nonlinear Dynamic Experimental Validation LSTM Model Delta XAI Stability Threshold

February 3, 2023

Physics-Informed Long Short-Term Memory for Forecasting and Reconstruction of Chaos
Elise Özalp, Georgios Margazoglou, Luca Magri
Long Short Term Memory LSTM Network Full State Reconstruction State of the Art Forecasting Kill Chaos LSTM Model

December 4, 2022

An LSTM model for Twitter Sentiment Analysis
Md Parvez Mollah
Sentiment Analysis Implicit Sentiment LSTM Model Tweet Text Sentiment Analysis Datasets Public Reaction

November 26, 2022

How Crucial is Transformer in Decision Transformer?
Max Siebenborn, Boris Belousov, Junning Huang, Jan Peters
Reinforcement Learning Transformer Based LSTM Network Decision Transformer LSTM Model

October 26, 2022

RapidAI4EO: Mono- and Multi-temporal Deep Learning models for Updating the CORINE Land Cover Product
Priyash Bhugra, Benjamin Bischke, Christoph Werner, Robert Syrnicki, Carolin Packbier, Patrick Helber, Caglar Senaras, Akhil Singh Rana, Tim Davis, Wanda De Keersmaecker, Daniele Zanaga, Annett Wania, Ruben Van De Kerchove, Giovanni Marchisio
Time Series Multi Label Classification LSTM Model Land Use Land Cover

October 21, 2022

Spoken Term Detection and Relevance Score Estimation using Dot-Product of Pronunciation Embeddings
Jan Švec, Luboš Šmídl, Josef V. Psutka, Aleš Pražák
LSTM Network LSTM Model Relevance Modeling Dot Product Phonetic Embeddings Spoken Term

September 28, 2022

Towards Automatic Forecasting: Evaluation of Time-Series Forecasting Models for Chickenpox Cases Estimation in Hungary
Wadie Skaf, Arzu Tosayeva, Dániel T. Várkonyi
Global Evaluation Time Series Forecasting LSTM Model Progression Prediction

July 6, 2022

Learning Optimal Solutions via an LSTM-Optimization Framework
Dogacan Yilmaz, İ. Esra Büyüktahtakın
Neural Network Long Short Term Memory LSTM Network Mixed Integer LSTM Model

June 29, 2022

DDKtor: Automatic Diadochokinetic Speech Analysis
Yael Segal, Kasia Hitczenko, Matthew Goldrick, Adam Buchwald, Angela Roberts, Joseph Keshet
LSTM Model Unlabeled Speech Speech Sound Disorder

June 3, 2022

Human Activity Recognition on Time Series Accelerometer Sensor Data using LSTM Recurrent Neural Networks
Chrisogonas O. Odhiambo, Sanjoy Saha, Corby K. Martin, Homayoun Valafar
Activity Recognition LSTM Network Sensor Data Sensor System LSTM Model Accelerometer Signal Accelerometer Data

May 21, 2022

LSTM-Based Adaptive Vehicle Position Control for Dynamic Wireless Charging
Lokesh Chandra Das, Dipankar Dasgupta, Myounggyu Won
LSTM Model Wireless Power Transfer Adaptive EV