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Found 6 papers, 1 papers with code
Continuous-time Particle Filtering for Latent Stochastic Differential Equations
Particle filtering is a standard Monte-Carlo approach for a wide range of sequential inference tasks.
Continuous Latent Process Flows
Partial observations of continuous time-series dynamics at arbitrary time stamps exist in many disciplines.
Unsupervised Video Decomposition using Spatio-temporal Iterative Inference
Unsupervised multi-object scene decomposition is a fast-emerging problem in representation learning.
Learning Physics-guided Face Relighting under Directional Light
Relighting is an essential step in realistically transferring objects from a captured image into another environment.
Traversing the Continuous Spectrum of Image Retrieval with Deep Dynamic Models
While the proposed approaches in the literature can be roughly categorized into two main groups: category- and instance-based retrieval, in this work we show that the retrieval task is much richer and more complex.
Efficient Nonlinear Markov Models for Human Motion
The use of hidden variables makes them expressive models, but inference is only approximate and requires procedures such as particle filters or Markov chain Monte Carlo methods.
