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TrajDiff: Trajectory Prediction With Diffusion Probabilistic Models
IEEE Transactions on Image ProcessingDiffusion probabilistic models (DPMs) have recently achieved brilliant achievements in computer vision. Inspired by the success of DPMs, we present TrajDiff, a model based on conditional diffusion probabilistic models for agent future trajectory ...
Changzhi Yang +3 more
semanticscholar +1 more source
Rethinking Flow and Diffusion Bridge Models for Speech Enhancement
AAAI Conference on Artificial IntelligenceFlow matching and diffusion bridge models have emerged as leading paradigms in generative speech enhancement, modeling stochastic processes between paired noisy and clean speech signals based on principles such as flow matching, score matching, and ...
Dahan Wang +6 more
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Fractional Diffusion Bridge Models
arXiv.orgWe present Fractional Diffusion Bridge Models (FDBM), a novel generative diffusion bridge framework driven by an approximation of the rich and non-Markovian fractional Brownian motion (fBM).
Gabriel Nobis +7 more
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Model-Based Spatial Data Fusion
Annual Review of Statistics and Its ApplicationWith increased data collection, the need to fuse data sources has emerged as an important and rapidly growing research activity in the statistical community.
Alan E. Gelfand, E. Schliep
semanticscholar +1 more source
Proceedings of 8th Mediterranean Electrotechnical Conference on Industrial Applications in Power Systems, Computer Science and Telecommunications (MELECON 96), 1996
A. Cavallini, G. Mazzanti, G. Montanari
semanticscholar +1 more source
A. Cavallini, G. Mazzanti, G. Montanari
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Harmonizable processes and inference: unbiased prediction for stochastic flows
, 1994M. Rao
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