Cover Image

Learning to Embed Time Series Patches Independently

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lee, Seunghan, Park, Taeyoung, Lee, Kibok
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Soft Contrastive Learning for Time Series
by: Lee, Seunghan, et al.
Published: (2023)

Channel Normalization for Time Series Channel Identification
by: Lee, Seunghan, et al.
Published: (2025)

Dataset-Driven Channel Masks in Transformers for Multivariate Time Series
by: Lee, Seunghan, et al.
Published: (2024)

ANT: Adaptive Noise Schedule for Time Series Diffusion Models
by: Lee, Seunghan, et al.
Published: (2024)

Sequential Order-Robust Mamba for Time Series Forecasting
by: Lee, Seunghan, et al.
Published: (2024)

To Predict or Not To Predict? Proportionally Masked Autoencoders for Tabular Data Imputation
by: Kim, Jungkyu, et al.
Published: (2024)

Mitigating Label Shift in Tabular In-Context Learning via Test-Time Posterior Adjustment
by: Lee, Seunghan
Published: (2026)

Enhancing Channel-Independent Time Series Forecasting via Cross-Variate Patch Embedding
by: Shin, Donghwa, et al.
Published: (2025)

On the Effectiveness of Supervision in Asymmetric Non-Contrastive Learning
by: Oh, Jeongheon, et al.
Published: (2024)

GTA: Generative Trajectory Augmentation with Guidance for Offline Reinforcement Learning
by: Lee, Jaewoo, et al.
Published: (2024)

FinTexTS: Financial Text-Paired Time-Series Dataset via Semantic-Based and Multi-Level Pairing
by: Lee, Jaehoon, et al.
Published: (2026)

FinSTaR: Towards Financial Reasoning with Time Series Reasoning Models
by: Lee, Seunghan, et al.
Published: (2026)

Rethinking Multimodal Fusion for Time Series: Auxiliary Modalities Need Constrained Fusion
by: Lee, Seunghan, et al.
Published: (2026)

PaAno: Patch-Based Representation Learning for Time-Series Anomaly Detection
by: Park, Jinju, et al.
Published: (2026)

IConv: Focusing on Local Variation with Channel Independent Convolution for Multivariate Time Series Forecasting
by: Lee, Gawon, et al.
Published: (2025)

Continuous-Time Linear Positional Embedding for Irregular Time Series Forecasting
by: Kim, Byunghyun, et al.
Published: (2024)

Guided Trajectory Generation with Diffusion Models for Offline Model-based Optimization
by: Yun, Taeyoung, et al.
Published: (2024)

When and Where to Reset Matters for Long-Term Test-Time Adaptation
by: Lim, Taejun, et al.
Published: (2026)

PatchDecomp: Interpretable Patch-Based Time Series Forecasting
by: Tomioka, Hiroki, et al.
Published: (2026)

TimeBridge: Better Diffusion Prior Design with Bridge Models for Time Series Generation
by: Park, Jinseong, et al.
Published: (2024)

Automated Kernel Discovery Towards Understanding High-dimensional Bayesian Optimization
by: Yun, Taeyoung, et al.
Published: (2026)

Are Self-Attentions Effective for Time Series Forecasting?
by: Kim, Dongbin, et al.
Published: (2024)

TimePerceiver: An Encoder-Decoder Framework for Generalized Time-Series Forecasting
by: Lee, Jaebin, et al.
Published: (2025)

Computer Vision Self-supervised Learning Methods on Time Series
by: Lee, Daesoo, et al.
Published: (2021)

T-Rep: Representation Learning for Time Series using Time-Embeddings
by: Fraikin, Archibald, et al.
Published: (2023)

Soft Task-Aware Routing of Experts for Equivariant Representation Learning
by: Jeon, Jaebyeong, et al.
Published: (2025)

Analysis of Fourier Neural Operators via Effective Field Theory
by: Kim, Taeyoung
Published: (2025)

Loop Corrections to the Training Error and Generalization Gap of Random Feature Models
by: Kim, Taeyoung
Published: (2026)

Unlocking the Power of Patch: Patch-Based MLP for Long-Term Time Series Forecasting
by: Tang, Peiwang, et al.
Published: (2024)

STEP: Learning STructured Embeddings for Progressive Time Series
by: Thil, Lucas, et al.
Published: (2026)

When Will It Fail?: Anomaly to Prompt for Forecasting Future Anomalies in Time Series
by: Park, Min-Yeong, et al.
Published: (2025)

JustDense: Just using Dense instead of Sequence Mixer for Time Series analysis
by: Park, TaekHyun, et al.
Published: (2025)

PatchTrAD: A Patch-Based Transformer focusing on Patch-Wise Reconstruction Error for Time Series Anomaly Detection
by: Vilhes, Samy-Melwan, et al.
Published: (2025)

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

SPQR: Controlling Q-ensemble Independence with Spiked Random Model for Reinforcement Learning
by: Lee, Dohyeok, et al.
Published: (2024)

Generating Multi-Table Time Series EHR from Latent Space with Minimal Preprocessing
by: Cho, Eunbyeol, et al.
Published: (2025)

A Scalable and Transferable Time Series Prediction Framework for Demand Forecasting
by: Park, Young-Jin, et al.
Published: (2024)

A New Perspective on Time Series Anomaly Detection: Faster Patch-based Broad Learning System
by: Li, Pengyu, et al.
Published: (2024)

CAFO: Feature-Centric Explanation on Time Series Classification
by: Kim, Jaeho, et al.
Published: (2024)

On the Regularization of Learnable Embeddings for Time Series Forecasting
by: Butera, Luca, et al.
Published: (2024)