3 papers
cs.LG2024
Recurrent Interpolants for Probabilistic Time Series Prediction
Yu Chen, Marin Biloš, Sarthak Mittal +3
Sequential models like recurrent neural networks and transformers have become standard for probabilistic multivariate time series forecasting across various domains. Despite their…
cs.LG2024
Variational Schrödinger Diffusion Models
Wei Deng, Weijian Luo, Yixin Tan +4
Schrödinger bridge (SB) has emerged as the go-to method for optimizing transportation plans in diffusion models. However, SB requires estimating the intractable forward score funct…
stat.ML2024
Reflected Schrödinger Bridge for Constrained Generative Modeling
Wei Deng, Yu Chen, Nicole Tianjiao Yang +3
Diffusion models have become the go-to method for large-scale generative models in real-world applications. These applications often involve data distributions confined within boun…