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stat.ML2025
Conditionally Whitened Generative Models for Probabilistic Time Series Forecasting
Yanfeng Yang, Siwei Chen, Pingping Hu +6
Probabilistic forecasting of multivariate time series is challenging due to non-stationarity, inter-variable dependencies, and distribution shifts. While recent diffusion and flow…
stat.ML2025
Diffusion Models with Double Guidance: Generate with aggregated datasets
Yanfeng Yang, Kenji Fukumizu
Creating large-scale datasets for training high-performance generative models is often prohibitively expensive, especially when associated attributes or annotations must be provide…
stat.ML2024
Conditional Diffusion Models Based Conditional Independence Testing
Yanfeng Yang, Shuai Li, Yingjie Zhang +4
Conditional independence (CI) testing is a fundamental task in modern statistics and machine learning. The conditional randomization test (CRT) was recently introduced to test whet…