Cover Image

Chimera: Effectively Modeling Multivariate Time Series with 2-Dimensional State Space Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Behrouz, Ali, Santacatterina, Michele, Zabih, Ramin
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

MambaMixer: Efficient Selective State Space Models with Dual Token and Channel Selection
by: Behrouz, Ali, et al.
Published: (2024)

Chimera: State Space Models Beyond Sequences
by: Lahoti, Aakash, et al.
Published: (2025)

Permutation-Equivariant 2D State Space Models: Theory and Canonical Architecture for Multivariate Time Series
by: Jeong, Seungwoo, et al.
Published: (2026)

UniTST: Effectively Modeling Inter-Series and Intra-Series Dependencies for Multivariate Time Series Forecasting
by: Liu, Juncheng, et al.
Published: (2024)

Are KANs Effective for Multivariate Time Series Forecasting?
by: Han, Xiao, et al.
Published: (2024)

Latent Space Score-based Diffusion Model for Probabilistic Multivariate Time Series Imputation
by: Liang, Guojun, et al.
Published: (2024)

TimePFN: Effective Multivariate Time Series Forecasting with Synthetic Data
by: Taga, Ege Onur, et al.
Published: (2025)

Time-SSM: Simplifying and Unifying State Space Models for Time Series Forecasting
by: Hu, Jiaxi, et al.
Published: (2024)

Falcon-X: A Time Series Foundation Model for Heterogeneous Multivariate Modeling
by: Liu, Yiding, et al.
Published: (2026)

TimeMKG: Knowledge-Infused Causal Reasoning for Multivariate Time Series Modeling
by: Sun, Yifei, et al.
Published: (2025)

Large Language Models are Few-shot Multivariate Time Series Classifiers
by: Chen, Yakun, et al.
Published: (2025)

MTSCI: A Conditional Diffusion Model for Multivariate Time Series Consistent Imputation
by: Zhou, Jianping, et al.
Published: (2024)

Context Neural Networks: A Scalable Multivariate Model for Time Series Forecasting
by: Sriramulu, Abishek, et al.
Published: (2024)

Efficient Linear Attention for Multivariate Time Series Modeling via Entropy Equality
by: Zhang, Mingtao, et al.
Published: (2025)

A Statistical Approach for Modeling Irregular Multivariate Time Series with Missing Observations
by: Nie, Dingyi, et al.
Published: (2026)

vLinear: A Powerful Linear Model for Multivariate Time Series Forecasting
by: Yue, Wenzhen, et al.
Published: (2026)

SSD-TS: Exploring the Potential of Linear State Space Models for Diffusion Models in Time Series Imputation
by: Gao, Hongfan, et al.
Published: (2024)

Joint Selective State Space Model and Detrending for Robust Time Series Anomaly Detection
by: Chen, Junqi, et al.
Published: (2024)

Time Series Clustering with General State Space Models via Stochastic Variational Inference
by: Ishizuka, Ryoichi, et al.
Published: (2024)

Forecast2Anomaly (F2A): Adapting Multivariate Time Series Foundation Models for Anomaly Prediction
by: Hassan, Atif, et al.
Published: (2025)

Investigating a Model-Agnostic and Imputation-Free Approach for Irregularly-Sampled Multivariate Time-Series Modeling
by: Neog, Abhilash, et al.
Published: (2025)

DARTs: A Dual-Path Robust Framework for Anomaly Detection in High-Dimensional Multivariate Time Series
by: Liu, Xuechun, et al.
Published: (2025)

mTSBench: Benchmarking Multivariate Time Series Anomaly Detection and Model Selection at Scale
by: Zhou, Xiaona, et al.
Published: (2025)

VLBM: Variational Latent Basis Modeling for OOD Robust Multivariate Time Series Forecasting
by: Zhang, Xudong, et al.
Published: (2026)

Revisiting Attention for Multivariate Time Series Forecasting
by: Wu, Haixiang
Published: (2024)

Nearest Neighbor Multivariate Time Series Forecasting
by: Zhang, Huiliang, et al.
Published: (2025)

Evaluating Time-Series Training Dataset through Lens of Spectrum in Deep State Space Models
by: Kanai, Sekitoshi, et al.
Published: (2024)

Mamba4Cast: Efficient Zero-Shot Time Series Forecasting with State Space Models
by: Bhethanabhotla, Sathya Kamesh, et al.
Published: (2024)

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

Titans: Learning to Memorize at Test Time
by: Behrouz, Ali, et al.
Published: (2024)

Multivariate Time Series Anomaly Detection by Capturing Coarse-Grained Intra- and Inter-Variate Dependencies
by: Xie, Yongzheng, et al.
Published: (2025)

E2USD: Efficient-yet-effective Unsupervised State Detection for Multivariate Time Series
by: Lai, Zhichen, et al.
Published: (2024)

Scalable Transformer for High Dimensional Multivariate Time Series Forecasting
by: Zhou, Xin, et al.
Published: (2024)

TimeDRL: Disentangled Representation Learning for Multivariate Time-Series
by: Chang, Ching, et al.
Published: (2023)

HTMformer: Hybrid Time and Multivariate Transformer for Time Series Forecasting
by: Wang, Tan, et al.
Published: (2025)

GinAR: An End-To-End Multivariate Time Series Forecasting Model Suitable for Variable Missing
by: Yu, Chengqing, et al.
Published: (2024)

ReFocus: Reinforcing Mid-Frequency and Key-Frequency Modeling for Multivariate Time Series Forecasting
by: Yu, Guoqi, et al.
Published: (2025)

Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics with Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis
by: Xu, Haowen, et al.
Published: (2024)

SCFormer: Structured Channel-wise Transformer with Cumulative Historical State for Multivariate Time Series Forecasting
by: Guo, Shiwei, et al.
Published: (2025)

It's All Connected: A Journey Through Test-Time Memorization, Attentional Bias, Retention, and Online Optimization
by: Behrouz, Ali, et al.
Published: (2025)