3 papers
cs.LG2025
Speculative Sampling for Parametric Temporal Point Processes
Marin Biloš, Anderson Schneider, Yuriy Nevmyvaka
Temporal point processes are powerful generative models for event sequences that capture complex dependencies in time-series data. They are commonly specified using autoregressive…
cs.LG2025
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 func…
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…