CAST: Context- and Anomaly Structure-Conditioned Time Series Anomaly Generation
cs.LG
Submitted: 2026-08-19
Updated: 2026-08-19
Code: https://github.com/UNITES-Lab/FlowTS
Terminology
Sources
- Neural Contextual Anomaly Detection for Time Series
- LTSM-Bundle: A Toolbox and Benchmark on Large Language Models for Time Series Forecasting
- GenIAS: Generator for Instantiating Anomalies in time Series
- TimeVAE: A Variational Auto-Encoder for Multivariate Time Series Generation
- A Diffusion Model for Regular Time Series Generation from Irregular Data with Completion and Masking
- RobustTAD: Robust Time Series Anomaly Detection via Decomposition and Convolutional Neural Networks
- MOMENT: A Family of Open Time-series Foundation Models
- FlowTS: Time Series Generation via Rectified Flow
- Robust PCA for Anomaly Detection in Cyber Networks
- Training-Free Time Series Classification via In-Context Reasoning with LLM Agents
- Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding
- TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis
- mixup: Beyond Empirical Risk Minimization
- Towards Stable and Structured Time Series Generation with Perturbation-Aware Flow Matching
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