Copertina

Enhancing Spatiotemporal Networks with xLSTM: A Scalar LSTM Approach for Cellular Traffic Forecasting

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Ali, Khalid, Bettouche, Zineddine, Kassler, Andreas, Fischer, Andreas
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

HiSTM: Hierarchical Spatiotemporal Mamba for Cellular Traffic Forecasting
di: Bettouche, Zineddine, et al.
Pubblicazione: (2025)

Spatial PDE-aware Selective State-space with Nested Memory for Mobile Traffic Grid Forecasting
di: Bettouche, Zineddine, et al.
Pubblicazione: (2026)

xLSTM: Extended Long Short-Term Memory
di: Beck, Maximilian, et al.
Pubblicazione: (2024)

xLSTMTime : Long-term Time Series Forecasting With xLSTM
di: Alharthi, Musleh, et al.
Pubblicazione: (2024)

xLSTM-ECG: Multi-label ECG Classification via Feature Fusion with xLSTM
di: Kang, Lei, et al.
Pubblicazione: (2025)

Vision-LSTM: xLSTM as Generic Vision Backbone
di: Alkin, Benedikt, et al.
Pubblicazione: (2024)

xLSTMAD: A Powerful xLSTM-based Method for Anomaly Detection
di: Faber, Kamil, et al.
Pubblicazione: (2025)

Distil-xLSTM: Learning Attention Mechanisms through Recurrent Structures
di: Thiombiano, Abdoul Majid O., et al.
Pubblicazione: (2025)

Seg-LSTM: Performance of xLSTM for Semantic Segmentation of Remotely Sensed Images
di: Zhu, Qinfeng, et al.
Pubblicazione: (2024)

Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequences
di: Schmidinger, Niklas, et al.
Pubblicazione: (2024)

Tiled Flash Linear Attention: More Efficient Linear RNN and xLSTM Kernels
di: Beck, Maximilian, et al.
Pubblicazione: (2025)

xLSTM 7B: A Recurrent LLM for Fast and Efficient Inference
di: Beck, Maximilian, et al.
Pubblicazione: (2025)

A Large Recurrent Action Model: xLSTM enables Fast Inference for Robotics Tasks
di: Schmied, Thomas, et al.
Pubblicazione: (2024)

MoxE: Mixture of xLSTM Experts with Entropy-Aware Routing for Efficient Language Modeling
di: Thiombiano, Abdoul Majid O., et al.
Pubblicazione: (2025)

Contextual Categorization Enhancement through LLMs Latent-Space
di: Bettouche, Zineddine, et al.
Pubblicazione: (2024)

xLSTM-SENet: xLSTM for Single-Channel Speech Enhancement
di: Kühne, Nikolai Lund, et al.
Pubblicazione: (2025)

Network Level Spatial Temporal Traffic State Forecasting with Hierarchical-Attention-LSTM (HierAttnLSTM)
di: Zhang, Tianya
Pubblicazione: (2022)

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images
di: Sahukara, Krishna, et al.
Pubblicazione: (2025)

xLSTM-Mixer: Multivariate Time Series Forecasting by Mixing via Scalar Memories
di: Kraus, Maurice, et al.
Pubblicazione: (2024)

Integrating Spatiotemporal Features in LSTM for Spatially Informed COVID-19 Hospitalization Forecasting
di: Wang, Zhongying, et al.
Pubblicazione: (2025)

Benchmarking Transformer and xLSTM for Time-Series Forecasting of Heat Consumption
di: Wahl, Marja, et al.
Pubblicazione: (2026)

WEST GCN-LSTM: Weighted Stacked Spatio-Temporal Graph Neural Networks for Regional Traffic Forecasting
di: Theodoropoulos, Theodoros, et al.
Pubblicazione: (2024)

Effective Distillation to Hybrid xLSTM Architectures
di: Hauzenberger, Lukas, et al.
Pubblicazione: (2026)

Cross-household Transfer Learning Approach with LSTM-based Demand Forecasting
di: Rahal, Manal, et al.
Pubblicazione: (2026)

Attention-Enhanced LSTM Modeling for Improved Temperature and Rainfall Forecasting in Bangladesh
di: Joy, Usman Gani, et al.
Pubblicazione: (2025)

Data-driven Insights for Informed Decision-Making: Applying LSTM Networks for Robust Electricity Forecasting in Libya
di: Agaal, Asma, et al.
Pubblicazione: (2025)

MolGraph-xLSTM: A graph-based dual-level xLSTM framework with multi-head mixture-of-experts for enhanced molecular representation and interpretability
di: Sun, Yan, et al.
Pubblicazione: (2025)

Incident-Guided Spatiotemporal Traffic Forecasting
di: Fan, Lixiang, et al.
Pubblicazione: (2026)

Optimizing LSTM Neural Networks for Resource-Constrained Retail Sales Forecasting: A Model Compression Study
di: Pagidoju, Ravi Teja
Pubblicazione: (2026)

xLSTM Scaling Laws: Competitive Performance with Linear Time-Complexity
di: Beck, Maximilian, et al.
Pubblicazione: (2025)

packetLSTM: Dynamic LSTM Framework for Streaming Data with Varying Feature Space
di: Agarwal, Rohit, et al.
Pubblicazione: (2024)

Spatiotemporal-aware Trend-Seasonality Decomposition Network for Traffic Flow Forecasting
di: Cao, Lingxiao, et al.
Pubblicazione: (2025)

Enhanced Photovoltaic Power Forecasting: An iTransformer and LSTM-Based Model Integrating Temporal and Covariate Interactions
di: Wu, Guang, et al.
Pubblicazione: (2024)

Evaluating the effectiveness of predicting covariates in LSTM Networks for Time Series Forecasting
di: Davies, Gareth
Pubblicazione: (2024)

Improving Traffic Flow Predictions with SGCN-LSTM: A Hybrid Model for Spatial and Temporal Dependencies
di: Cismaru, Alexandru T.
Pubblicazione: (2024)

Hybrid SARIMA LSTM Model for Local Weather Forecasting: A Residual Learning Approach for Data Driven Meteorological Prediction
di: Rajeev, Shreyas, et al.
Pubblicazione: (2026)

Evaluating the Sensitivity of BiLSTM Forecasting Models to Sequence Length and Input Noise
di: Albelali, Salma, et al.
Pubblicazione: (2025)

APS-LSTM: Exploiting Multi-Periodicity and Diverse Spatial Dependencies for Flood Forecasting
di: Feng, Jun, et al.
Pubblicazione: (2024)

xLSTM-PINN: Memory-Gated Spectral Remodeling for Physics-Informed Learning
di: Tao, Ze, et al.
Pubblicazione: (2025)

A Deep Reinforcement Learning Approach to Automated Stock Trading, using xLSTM Networks
di: Sarlakifar, Faezeh, et al.
Pubblicazione: (2025)