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Time Series Generation

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Showing 1–50 of 87 papers

TitleStatusHype
Diffusion-TS: Interpretable Diffusion for General Time Series GenerationCode3
Time-series Transformer Generative Adversarial NetworksCode3
T2S: High-resolution Time Series Generation with Text-to-Series Diffusion ModelsCode2
Closing the Gap Between Synthetic and Ground Truth Time Series Distributions via Neural MappingCode2
Diffusion Transformers for Tabular Data Time Series GenerationCode1
Population Aware Diffusion for Time Series GenerationCode1
FM-TS: Flow Matching for Time Series GenerationCode1
SeriesGAN: Time Series Generation via Adversarial and Autoregressive LearningCode1
ChronoGAN: Supervised and Embedded Generative Adversarial Networks for Time Series GenerationCode1
Time-Transformer: Integrating Local and Global Features for Better Time Series GenerationCode1
Explainable Time Series Anomaly Detection using Masked Latent Generative ModelingCode1
Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEsCode1
TSGBench: Time Series Generation BenchmarkCode1
Non-adversarial training of Neural SDEs with signature kernel scoresCode1
PCF-GAN: generating sequential data via the characteristic function of measures on the path spaceCode1
Vector Quantized Time Series Generation with a Bidirectional Prior ModelCode1
Causal Recurrent Variational Autoencoder for Medical Time Series GenerationCode1
Deep Latent State Space Models for Time-Series GenerationCode1
Transformer-based conditional generative adversarial network for multivariate time series generationCode1
Multi-Label Clinical Time-Series Generation via Conditional GANCode1
Time Series Generation with Masked AutoencoderCode1
TimeVAE: A Variational Auto-Encoder for Multivariate Time Series GenerationCode1
Sig-Wasserstein GANs for Time Series GenerationCode1
Monte Carlo Simulation of SDEs using GANsCode1
MTSS-GAN: Multivariate Time Series Simulation Generative Adversarial NetworksCode1
Conditional Sig-Wasserstein GANs for Time Series GenerationCode1
EEG-GAN: Generative adversarial networks for electroencephalograhic (EEG) brain signalsCode1
How to Unlock Time Series Editing? Diffusion-Driven Approach with Multi-Grained Control—0
Trajectory Generator Matching for Time Series—0
Forging Time Series with Language: A Large Language Model Approach to Synthetic Data Generation—0
MSDformer: Multi-scale Discrete Transformer For Time Series Generation—0
Challenges and Limitations in the Synthetic Generation of mHealth Sensor Data—0
Diffusion-assisted Model Predictive Control Optimization for Power System Real-Time Operation—0
TarDiff: Target-Oriented Diffusion Guidance for Synthetic Electronic Health Record Time Series Generation—0
Theoretical Foundation of Flow-Based Time Series Generation: Provable Approximation, Generalization, and Efficiency—0
WaveStitch: Flexible and Fast Conditional Time Series Generation with Diffusion ModelsCode0
CoFinDiff: Controllable Financial Diffusion Model for Time Series Generation—0
BRIDGE: Bootstrapping Text to Control Time-Series Generation via Multi-Agent Iterative Optimization and Diffusion Modeling—0
Robust time series generation via Schrödinger Bridge: a comprehensive evaluation—0
CENTS: Generating synthetic electricity consumption time series for rare and unseen scenarios—0
Time series forecasting for multidimensional telemetry data using GAN and BiLSTM in a Digital Twin—0
TimeDP: Learning to Generate Multi-Domain Time Series with Domain Prompts—0
AVATAR: Adversarial Autoencoders with Autoregressive Refinement for Time Series GenerationCode0
LeMoLE: LLM-Enhanced Mixture of Linear Experts for Time Series Forecasting—0
PATH: A Discrete-sequence Dataset for Evaluating Online Unsupervised Anomaly Detection Approaches for Multivariate Time SeriesCode0
IMUDiffusion: A Diffusion Model for Multivariate Time Series Synthetisation for Inertial Motion Capturing Systems—0
Federated Time Series Generation on Feature and Temporally Misaligned Data—0
Constrained Posterior Sampling: Time Series Generation with Hard Constraints—0
Exploring Fungal Morphology Simulation and Dynamic Light Containment from a Graphics Generation Perspective—0
Blending Low and High-Level Semantics of Time Series for Better Masked Time Series Generation—0
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