Cover Image

xLSTM-Mixer: Multivariate Time Series Forecasting by Mixing via Scalar Memories

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kraus, Maurice, Divo, Felix, Dhami, Devendra Singh, Kersting, Kristian
Format:	Preprint
Published:	2024
Subjects:	Machine Learning I.2.6
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Exploring Neural Granger Causality with xLSTMs: Unveiling Temporal Dependencies in Complex Data
by: Poonia, Harsh, et al.
Published: (2025)

QuAnTS: Question Answering on Time Series
by: Divo, Felix, et al.
Published: (2025)

Forecasting Company Fundamentals
by: Divo, Felix, et al.
Published: (2024)

United We Pretrain, Divided We Fail! Representation Learning for Time Series by Pretraining on 75 Datasets at Once
by: Kraus, Maurice, et al.
Published: (2024)

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

Self-Expanding Neural Networks
by: Mitchell, Rupert, et al.
Published: (2023)

Distributional Drift Adaptation with Temporal Conditional Variational Autoencoder for Multivariate Time Series Forecasting
by: He, Hui, et al.
Published: (2022)

Graph Neural Networks Need Cluster-Normalize-Activate Modules
by: Skryagin, Arseny, et al.
Published: (2024)

Robust Multivariate Time Series Forecasting against Intra- and Inter-Series Transitional Shift
by: He, Hui, et al.
Published: (2024)

NoRIN: Backbone-Adaptive Reversible Normalization for Time-Series Forecasting
by: Zhang, Shun, et al.
Published: (2026)

TimeCatcher: A Variational Framework for Volatility-Aware Forecasting of Non-Stationary Time Series
by: Chen, Zhiyu, et al.
Published: (2026)

Entropy Causal Graphs for Multivariate Time Series Anomaly Detection
by: Febrinanto, Falih Gozi, et al.
Published: (2023)

KAN vs LSTM Performance in Time Series Forecasting
by: Rather, Tabish Ali, et al.
Published: (2025)

Adaptable Hindsight Experience Replay for Search-Based Learning
by: Vazaios, Alexandros, et al.
Published: (2025)

GCAD: Anomaly Detection in Multivariate Time Series from the Perspective of Granger Causality
by: Liu, Zehao, et al.
Published: (2025)

Deep Memory Search: A Metaheuristic Approach for Optimizing Heuristic Search
by: Hedar, Abdel-Rahman, et al.
Published: (2024)

Superposition Is Not Necessary: A Mechanistic Interpretability Analysis of Transformer Representations for Time Series Forecasting
by: Yıldırım, Alper
Published: (2026)

Inter-Series Transformer: Attending to Products in Time Series Forecasting
by: Cristian, Rares, et al.
Published: (2024)

DRFormer: Multi-Scale Transformer Utilizing Diverse Receptive Fields for Long Time-Series Forecasting
by: Ding, Ruixin, et al.
Published: (2024)

Symbol-Temporal Consistency Self-supervised Learning for Robust Time Series Classification
by: Garcia, Kevin, et al.
Published: (2025)

Counterfactual Explanation for Multivariate Time Series Forecasting with Exogenous Variables
by: Kinjo, Keita
Published: (2025)

Are We Winning the Wrong Game? Revisiting Evaluation Practices for Long-Term Time Series Forecasting
by: Phungtua-eng, Thanapol, et al.
Published: (2026)

Fusing Rewards and Preferences in Reinforcement Learning
by: Khorasani, Sadegh, et al.
Published: (2025)

Diffusion-Based Scenario Tree Generation for Multivariate Time Series Prediction and Multistage Stochastic Optimization
by: Zarifis, Stelios, et al.
Published: (2025)

Giving Sensors a Voice: Multimodal JEPA for Semantic Time-Series Embeddings
by: Dutta, Utsav, et al.
Published: (2026)

Remaining Useful Life Estimation for Turbofan Engines: A Comparative Study of Classical, CNN, and LSTM Approaches
by: Goel, Astitva, et al.
Published: (2026)

Neural Concept Verifier: Scaling Prover-Verifier Games via Concept Encodings
by: Turan, Berkant, et al.
Published: (2025)

DecompKAN: Decomposed Patch-KAN for Long-Term Time Series Forecasting
by: Mysore, Naveen
Published: (2026)

Inference-Time Machine Unlearning via Gated Activation Redirection
by: Turani, Vinícius Conte, et al.
Published: (2026)

Multipole Semantic Attention: A Fast Approximation of Softmax Attention for Pretraining
by: Mitchell, Rupert, et al.
Published: (2025)

Universal Approximation of Continuous Functionals on Compact Subsets via Linear Measurements and Scalar Nonlinearities
by: Krylov, Andrey, et al.
Published: (2026)

TFMAdapter: Lightweight Instance-Level Adaptation of Foundation Models for Forecasting with Covariates
by: Dange, Afrin, et al.
Published: (2025)

Forecasting Anomaly Precursors via Uncertainty-Aware Time-Series Ensembles
by: Kang, Hyeongwon, et al.
Published: (2026)

Energy and Memory-Efficient Federated Learning With Ordered Layer Freezing
by: Niu, Ziru, et al.
Published: (2025)

Annot-Mix: Learning with Noisy Class Labels from Multiple Annotators via a Mixup Extension
by: Herde, Marek, et al.
Published: (2024)

Bayesian Hierarchical Probabilistic Forecasting of Intraday Electricity Prices
by: Nickelsen, Daniel, et al.
Published: (2024)

tempdisagg: A Python Framework for Temporal Disaggregation of Time Series Data
by: Vera-Jaramillo, Jaime
Published: (2025)

RG-TTA: Regime-Guided Meta-Control for Test-Time Adaptation in Streaming Time Series
by: Kumar, Indar, et al.
Published: (2026)

Enhanced Random Subspace Local Projections for High-Dimensional Time Series Analysis
by: Khalid, Eman, et al.
Published: (2026)

TS-ACL: Closed-Form Solution for Time Series-oriented Continual Learning
by: Li, Jiaxu, et al.
Published: (2024)