Cover Image

xLSTMTime : Long-term Time Series Forecasting With xLSTM

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Alharthi, Musleh, Mahmood, Ausif
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

EMTSF:Extraordinary Mixture of SOTA Models for Time Series Forecasting
by: Alharthi, Musleh, et al.
Published: (2025)

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

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

Enhancing Spatiotemporal Networks with xLSTM: A Scalar LSTM Approach for Cellular Traffic Forecasting
by: Ali, Khalid, et al.
Published: (2025)

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

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

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

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

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

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

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

CacheFormer: High Attention-Based Segment Caching
by: Singh, Sushant, et al.
Published: (2025)

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

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

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

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

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

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

Mixture-of-Linear-Experts for Long-term Time Series Forecasting
by: Ni, Ronghao, et al.
Published: (2023)

Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping
by: Li, Zhe, et al.
Published: (2023)

SageFormer: Series-Aware Framework for Long-term Multivariate Time Series Forecasting
by: Zhang, Zhenwei, et al.
Published: (2023)

xPatch: Dual-Stream Time Series Forecasting with Exponential Seasonal-Trend Decomposition
by: Stitsyuk, Artyom, et al.
Published: (2024)

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

To See Far, Look Close: Evolutionary Forecasting for Long-term Time Series
by: Ma, Jiaming, et al.
Published: (2026)

MoHETS: Long-term Time Series Forecasting with Mixture-of-Heterogeneous-Experts
by: Ortigossa, Evandro S., et al.
Published: (2026)

TimelyGPT: Extrapolatable Transformer Pre-training for Long-term Time-Series Forecasting in Healthcare
by: Song, Ziyang, et al.
Published: (2023)

Leveraging 2D Information for Long-term Time Series Forecasting with Vanilla Transformers
by: Cheng, Xin, et al.
Published: (2024)

DySCo: Dynamic Semantic Compression for Effective Long-term Time Series Forecasting
by: Ao, Xiang, et al.
Published: (2026)

TimeKAN: KAN-based Frequency Decomposition Learning Architecture for Long-term Time Series Forecasting
by: Huang, Songtao, et al.
Published: (2025)

MambaTS: Improved Selective State Space Models for Long-term Time Series Forecasting
by: Cai, Xiuding, et al.
Published: (2024)

PENGUIN: Enhancing Transformer with Periodic-Nested Group Attention for Long-term Time Series Forecasting
by: Sun, Tian, et al.
Published: (2025)

MoDEx: Mixture of Depth-specific Experts for Multivariate Long-term Time Series Forecasting
by: Yoon, Hyekyung, et al.
Published: (2026)

A lightweight Spatial-Temporal Graph Neural Network for Long-term Time Series Forecasting
by: Moges, Henok Tenaw, et al.
Published: (2025)

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

Long Input Sequence Network for Long Time Series Forecasting
by: Ma, Chao, et al.
Published: (2024)

Breaking the Context Bottleneck on Long Time Series Forecasting
by: Ma, Chao, et al.
Published: (2024)

There are no Champions in Supervised Long-Term Time Series Forecasting
by: Brigato, Lorenzo, et al.
Published: (2025)

Quantum Kernel-Based Long Short-term Memory for Climate Time-Series Forecasting
by: Hsu, Yu-Chao, et al.
Published: (2024)

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

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