Diffusion Model时间序列相关的文章

Forecasting and Prediction

• Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting, in ICML 2021. [paper]
• ScoreGrad: Multivariate Probabilistic Time Series Forecasting with Continuous Energy-based Generative Models, in arXiv 2021. [paper]
• Generative Time Series Forecasting with Diffusion, Denoise, and Disentanglement, in NeurIPS 2022. [paper]
• Diffusion Variational Autoencoder for Tackling Stochasticity in Multi-Step Regression Stock Price Prediction, in CIKM 2023. [paper]
• Modeling Temporal Data as Continuous Functions with Process Diffusion, in ICML 2023. [paper]
• Non-autoregressive Conditional Diffusion Models for Time Series Prediction, in ICML 2023. [paper]
• DiffECG: A Generalized Probabilistic Diffusion Model for ECG Signals Synthesis, in arXiv 2023. [paper]
• Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting, in arXiv 2023. [paper]
• Data Augmentation for Seizure Prediction with Generative Diffusion Model, in arXiv 2023. [paper]
• DiffLoad: Uncertainty Quantification in Load Forecasting with Diffusion Model, in arXiv 2023. [paper]
• Denoising Diffusion Probabilistic Models for Probabilistic Energy Forecasting, in arXiv 2023. [paper]
• TDSTF: Transformer-based Diffusion probabilistic model for Sparse Time series Forecasting, in arXiv 2023. [paper]
• Graph Convolution Recurrent Denoising Diffusion Model for Multivariate Probabilistic Temporal Forecasting, Working Paper 2023. [link]

Generation

• WaveGrad: Estimating Gradients for Waveform Generation, in ICLR 2021. [paper]
• Diffusing Gaussian Mixtures for Generating Categorical Data, in AAAI 2023. [paper]
• Diffusion Generative Models in Infinite Dimensions, in AISTATS 2023. [paper]
• Conditioning Score-Based Generative Models by Neuro-Symbolic Constraints, in arXiv 2023. [paper]
• TransFusion: Generating Long, High Fidelity Time Series using Diffusion Models with Transformers, in arXiv 2023. [paper]
• On the Constrained Time-Series Generation Problem, in arXiv 2023. [paper]
• DiffECG: A Generalized Probabilistic Diffusion Model for ECG Signals Synthesis, in arXiv 2023. [paper]
• Customized Load Profiles Synthesis for Electricity Customers Based on Conditional Diffusion Models, in arXiv 2023. [paper]
• Synthetic Health-related Longitudinal Data with Mixed-type Variables Generated using Diffusion Models, in arXiv 2023. [paper]
• EHRDiff: Exploring Realistic EHR Synthesis with Diffusion Models, in arXiv 2023. [paper]
• Synthesizing Mixed-type Electronic Health Records using Diffusion Models, in arXiv 2023. [paper]
• MedDiff: Generating Electronic Health Records using Accelerated Denoising Diffusion Model, in arXiv 2023. [paper]

Imputation

• CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation, in NeurIPS 2021. [paper]
• Modeling Temporal Data as Continuous Functions with Process Diffusion, in ICML 2023. [paper]
• An Observed Value Consistent Diffusion Model for Imputing Missing Values in Multivariate Time Series, in KDD 2023. [paper]
• Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models, in Transactions on Machine Learning Research (TMLR) 2023. [paper]
• Sasdim: Self-adaptive Noise Scaling Diffusion Model for Spatial Time Series Imputation, in arXiv 2023. [paper]

Anomaly Detection

• Imputation-based Time-Series Anomaly Detection with Conditional Weight-Incremental Diffusion Models, in KDD 2023. [paper]
• ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly Detection, in arXiv 2023. [paper]

Classification and Regression

• CARD: Classification and Regression Diffusion Models, in NeurIPS 2022. [paper]

Causal Inference

• Diffusion Model in Causal Inference with Unmeasured Confounders, in arXiv 2023. [paper]

Diffusion Model for SpatioTemporal Data

• Spatio-temporal Diffusion Point Processes, in KDD 2023. [paper]
• DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting, in NeurIPS 2023. [paper]
• Extraction and Recovery of Spatio-Temporal Structure in Latent Dynamics Alignment with Diffusion Model, in NeurIPS 2023. [paper]
• DiffSTG: Probabilistic Spatio-Temporal Graph with Denoising Diffusion Models, in SIGSPATIAL 2023. [paper]
• PriSTI: A Conditional Diffusion Framework for Spatiotemporal Imputation, in ICDE 2023. [paper]
• Dynamic Causal Explanation Based Diffusion-Variational Graph Neural Network for Spatio-temporal Forecasting, in arXiv 2023. [paper]
• Sasdim: Self-adaptive Noise Scaling Diffusion Model for Spatial Time Series Imputation, in arXiv 2023. [paper]
• Imputation as Inpainting: Diffusion Models for Spatiotemporal Data Imputation, in OpenReview 2023. [paper]

Diffusion Model for Tabular Data

• Diffusion Models for Missing Value Imputation in Tabular Data, in NeurIPS TRL Workshop 2022. [paper]
• MissDiff: Training Diffusion Models on Tabular Data with Missing Values, in ICML Workshop 2023. [paper]
• CoDi: Co-evolving Contrastive Diffusion Models for Mixed-type Tabular Synthesis, in ICML 2023. [paper]
• TabDDPM: Modelling Tabular Data with Diffusion Models, in ICML 2023. [paper]
• Conditioning Score-Based Generative Models by Neuro-Symbolic Constraints, in arXiv 2023. [paper]
• On Diffusion Modeling for Anomaly Detection, in arXiv 2023. [paper]
• Generating Tabular Datasets under Differential Privacy, in arXiv 2023. [paper]
• TabADM: Unsupervised Tabular Anomaly Detection with Diffusion Models, in arXiv 2023. [paper]
• FinDiff: Diffusion Models for Financial Tabular Data Generation, in arXiv 2023. [paper]

Energy and Electricity

• DiffCharge: Generating EV Charging Scenarios via a Denoising Diffusion Model, in arXiv 2023. [paper]
• Customized Load Profiles Synthesis for Electricity Customers Based on Conditional Diffusion Models, in arXiv 2023. [paper]
• DiffLoad: Uncertainty Quantification in Load Forecasting with Diffusion Model, in arXiv 2023. [paper]
• Denoising Diffusion Probabilistic Models for Probabilistic Energy Forecasting, in arXiv 2023. [paper]

Math and Physics

• A Physics-informed Diffusion Model for High-fidelity Flow Field Reconstruction, in Journal of Computational Physics 2023. [paper]
• DiTTO: Diffusion-inspired Temporal Transformer Operator, in arXiv 2023. [paper]
• Infinite-dimensional Diffusion Models for Function Spaces, in arXiv 2023. [paper]
• Generative Diffusion Learning for Parametric Partial Differential Equations, in arXiv 2023. [paper]

Finance

• Diffusion Variational Autoencoder for Tackling Stochasticity in Multi-Step Regression Stock Price Prediction, in CIKM 2023. [paper]
• FinDiff: Diffusion Models for Financial Tabular Data Generation, in arXiv 2023. [paper]

AIOps

• Maat: Performance Metric Anomaly Anticipation for Cloud Services with Conditional Diffusion, in IEEE/ACM International Conference on Automated Software Engineering 2023. [paper]
• NetDiffus: Network Traffic Generation by Diffusion Models through Time-Series Imaging, in arXiv 2023. [paper]

Human

• Unsupervised Statistical Feature-Guided Diffusion Model for Sensor-based Human Activity Recognition, in arXiv 2023. [paper]

Environment

• Deep Diffusion Models for Seismic Processing, in Computers & Geosciences 2023. [paper]

博士，担任《Mechanical System and Signal Processing》审稿专家，担任
《中国电机工程学报》优秀审稿专家，《控制与决策》，《系统工程与电子技术》等EI期刊审稿专家，担任《计算机科学》，《电子器件》 ， 《现代制造过程》 ，《船舶工程》 ，《轴承》 ，《工矿自动化》 ，《重庆理工大学学报》 ，《噪声与振动控制》 ，《机械传动》 ，《机械强度》 ，《机械科学与技术》 ，《机床与液压》，《声学技术》，《应用声学》，《石油机械》，《西安工业大学学报》等中文核心审稿专家。
擅长领域：现代信号处理，机器学习，深度学习，数字孪生，时间序列分析，设备缺陷检测、设备异常检测、设备智能故障诊断与健康管理PHM等。