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Methods/LSTM

LSTM

Long Short-Term Memory

SequentialIntroduced 19975448 papers

Description

An LSTM is a type of recurrent neural network that addresses the vanishing gradient problem in vanilla RNNs through additional cells, input and output gates. Intuitively, vanishing gradients are solved through additional additive components, and forget gate activations, that allow the gradients to flow through the network without vanishing as quickly.

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(Introduced by Hochreiter and Schmidhuber)

Papers Using This Method

AI-Based Demand Forecasting and Load Balancing for Optimising Energy use in Healthcare Systems: A real case study2025-07-08A Hybrid Machine Learning Framework for Optimizing Crop Selection via Agronomic and Economic Forecasting2025-07-06MambAttention: Mamba with Multi-Head Attention for Generalizable Single-Channel Speech Enhancement2025-07-01Show, Tell and Summarize: Dense Video Captioning Using Visual Cue Aided Sentence Summarization2025-06-25Dense Video Captioning using Graph-based Sentence Summarization2025-06-25FINN-GL: Generalized Mixed-Precision Extensions for FPGA-Accelerated LSTMs2025-06-25Efficacy of Temporal Fusion Transformers for Runoff Simulation2025-06-25CoVE: Compressed Vocabulary Expansion Makes Better LLM-based Recommender Systems2025-06-24Emotion Detection on User Front-Facing App Interfaces for Enhanced Schedule Optimization: A Machine Learning Approach2025-06-24Simulation of a closed-loop dc-dc converter using a physics-informed neural network-based model2025-06-23Programmable-Room: Interactive Textured 3D Room Meshes Generation Empowered by Large Language Models2025-06-21Exploring Speaker Diarization with Mixture of Experts2025-06-17Intelligent Image Sensing for Crime Analysis: A ML Approach towards Enhanced Violence Detection and Investigation2025-06-16Seq2Bind Webserver for Decoding Binding Hotspots directly from Sequences using Fine-Tuned Protein Language Models2025-06-16Transforming Chatbot Text: A Sequence-to-Sequence Approach2025-06-15Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows2025-06-12Brain2Vec: A Deep Learning Framework for EEG-Based Stress Detection Using CNN-LSTM-Attention2025-06-12Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME2025-06-11Improving the performance of optical inverse design of multilayer thin films using CNN-LSTM tandem neural networks2025-06-11Cross-Learning Between ECG and PCG: Exploring Common and Exclusive Characteristics of Bimodal Electromechanical Cardiac Waveforms2025-06-11