Krahasoni metodat

	Inferenca Variacionale Dinamike	Filtrimi Kalman
Fusha	Statistika bajesiane	Statistika bajesiane
Familja	Bayesian methods	Bayesian methods
Viti i origjinës	2014–2015	1960
Krijuesi	Bayer, Osendorfer, Krishnan and colleagues	Rudolf E. Kalman
Lloji	Bayesian approximate inference	recursive Bayesian filter
Burimi themelues	Krishnan, R. G., Shalit, U., & Sontag, D. (2015). Deep Kalman Filters. NIPS 2015 Workshop on Advances in Approximate Bayesian Inference.	Kalman, R. E. (1960). A new approach to linear filtering and prediction problems. Journal of Basic Engineering, 82(1), 35-45.
Emërtime të tjera	sequential variational inference, temporal variational inference, variational inference for state-space models, DVI	linear quadratic estimator, LQE, Kalman-Bucy filter, optimal recursive filter
Të lidhura	6	5
Përmbledhja	Dynamic variational inference extends the variational inference framework to sequential and time-series settings by positing a structured approximate posterior that respects the temporal ordering of latent states. It jointly learns a generative model of how hidden states evolve over time and a recognition network that maps observed sequences back to those latent states, optimising a sequential evidence lower bound (ELBO).	The Kalman filter is an optimal recursive algorithm for estimating the hidden state of a linear dynamical system from noisy measurements. At each time step it alternates between a prediction step — projecting the state forward using the system model — and an update step that corrects the prediction with the new observation, producing minimum-variance state estimates and their uncertainty in real time.