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Found 5 papers, 1 papers with code
Last layer state space model for representation learning and uncertainty quantification
As sequential neural architectures become deeper and more complex, uncertainty estimation is more and more challenging.
Variational latent discrete representation for time series modelling
Discrete latent space models have recently achieved performance on par with their continuous counterparts in deep variational inference.
End-to-end deep meta modelling to calibrate and optimize energy consumption and comfort
Parameters are estimated by comparing the predictions of the metamodel with real data obtained from sensors using the CMA-ES algorithm, a derivative free optimization procedure.
End-to-end deep metamodeling to calibrate and optimize energy loads
Finally, the optimal settings to minimize the energy loads while maintaining a target thermal comfort and air quality are obtained using a multi-objective optimization procedure.
3D Face Pose and Animation Tracking via Eigen-Decomposition based Bayesian Approach
This paper presents a new method to track both the face pose and the face animation with a monocular camera.
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