Cover Image

TimeBridge: Better Diffusion Prior Design with Bridge Models for Time Series Generation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Park, Jinseong, Lee, Seungyun, Jeong, Woojin, Choi, Yujin, Lee, Jaewook
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

BayesNAM: Leveraging Inconsistency for Reliable Explanations
by: Kim, Hoki, et al.
Published: (2024)

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

Stability Analysis of Sharpness-Aware Minimization
by: Kim, Hoki, et al.
Published: (2023)

Multi-Class Support Vector Machine with Differential Privacy
by: Park, Jinseong, et al.
Published: (2025)

Leveraging Programmatically Generated Synthetic Data for Differentially Private Diffusion Training
by: Choi, Yujin, et al.
Published: (2024)

Fair Sampling in Diffusion Models through Switching Mechanism
by: Choi, Yujin, et al.
Published: (2024)

Data Unlearning Beyond Uniform Forgetting via Diffusion Time and Frequency Selection
by: Park, Jinseong, et al.
Published: (2025)

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

TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting
by: Liu, Peiyuan, et al.
Published: (2024)

SeMoBridge: Semantic Modality Bridge for Efficient Few-Shot Adaptation of CLIP
by: Timmermann, Christoph, et al.
Published: (2025)

Bridging Past and Future: Distribution-Aware Alignment for Time Series Forecasting
by: Hu, Yifan, et al.
Published: (2025)

Series-to-Series Diffusion Bridge Model
by: Yang, Hao, et al.
Published: (2024)

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)

Learning to Embed Time Series Patches Independently
by: Lee, Seunghan, et al.
Published: (2023)

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

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

MaD-Scientist: AI-based Scientist solving Convection-Diffusion-Reaction Equations Using Massive PINN-Based Prior Data
by: Kang, Mingu, et al.
Published: (2024)

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

Machine Unlearning for Masked Diffusion Language Models
by: Lee, Georu, et al.
Published: (2026)

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

Bridging Neural Networks and Dynamic Time Warping for Adaptive Time Series Classification
by: Qu, Jintao, et al.
Published: (2025)

Fast Ensembling with Diffusion Schrödinger Bridge
by: Kim, Hyunsu, et al.
Published: (2024)

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

Bridging Classification and Reconstruction: Cooperative Time Series Anomaly Detection
by: Tang, Qideng, et al.
Published: (2026)

Bridging Distribution Gaps in Time Series Foundation Model Pretraining with Prototype-Guided Normalization
by: Gong, Peiliang, et al.
Published: (2025)

SimDiff: Simpler Yet Better Diffusion Model for Time Series Point Forecasting
by: Ding, Hang, et al.
Published: (2025)

Kolmogorov-Arnold Networks for Time Series: Bridging Predictive Power and Interpretability
by: Xu, Kunpeng, et al.
Published: (2024)

Generative Pre-Training of Time-Series Data for Unsupervised Fault Detection in Semiconductor Manufacturing
by: Lee, Sewoong, et al.
Published: (2023)

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

PriorZero: Bridging Language Priors and World Models for Decision Making
by: Xiong, Junyu, et al.
Published: (2026)

Bridging the Gap: A Decade Review of Time-Series Clustering Methods
by: Paparrizos, John, et al.
Published: (2024)

TimeDiT: General-purpose Diffusion Transformers for Time Series Foundation Model
by: Cao, Defu, et al.
Published: (2024)

Thoth: Mid-Training Bridges LLMs to Time Series Understanding
by: Lin, Jiafeng, et al.
Published: (2026)

Dominating vs. Dominated: Generative Collapse in Diffusion Models
by: Jeong, Hayeon, et al.
Published: (2025)

Time-Transformer: Integrating Local and Global Features for Better Time Series Generation (Extended Version)
by: Liu, Yuansan, et al.
Published: (2023)

LoMETab: Beyond Rank-1 Ensembles for Tabular Deep Learning
by: Choi, Changryeol, et al.
Published: (2026)

Diffusion-TS: Interpretable Diffusion for General Time Series Generation
by: Yuan, Xinyu, et al.
Published: (2024)

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models
by: Ge, Yunfeng, et al.
Published: (2025)

Structured Diffusion Bridges: Inductive Bias for Denoising Diffusion Bridges
by: Kosman, Eitan, et al.
Published: (2026)