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State Space Models

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Showing 751–800 of 923 papers

TitleStatusHype
Probabilistic Transformer For Time Series Analysis—0
Likelihood-Free Inference in State-Space Models with Unknown DynamicsCode0
Efficient Learning of the Parameters of Non-Linear Models using Differentiable Resampling in Particle Filters—0
Explicit Port-Hamiltonian FEM-Models for Linear Mechanical Systems with Non-Uniform Boundary Conditions—0
Iterated Block Particle Filter for High-dimensional Parameter Learning: Beating the Curse of Dimensionality—0
State-Space Models Win the IEEE DataPort Competition on Post-covid Day-ahead Electricity Load Forecasting—0
Variational Marginal Particle FiltersCode0
Non asymptotic estimation lower bounds for LTI state space models with Cramér-Rao and van Trees—0
Blind Identification of State-Space Models in Physical Coordinates—0
Active Learning in Gaussian Process State Space Model—0
Self-Supervised Inference in State-Space Models—0
Hida-Matérn Kernel—0
Predictive Control Using Learned State Space Models via Rolling Horizon Evolution—0
Basis transform in switched linear system state-space models from input-output data—0
Generalized AdaGrad (G-AdaGrad) and Adam: A State-Space Perspective—0
Unbiased Estimation of the Gradient of the Log-Likelihood for a Class of Continuous-Time State-Space Models—0
Embedding Information onto a Dynamical System—0
PNLSS Toolbox 1.0—0
Hardware Synthesis of State-Space Equations; Application to FPGA Implementation of Shallow and Deep Neural NetworksCode0
Stochastic Recurrent Neural Network for Multistep Time Series Forecasting—0
Viking: Variational Bayesian Variance Tracking—0
Improved Initialization of State-Space Artificial Neural Networks—0
PAC-Bayesian theory for stochastic LTI systems—0
Smoothing-Averse Control: Covertness and Privacy from Smoothers—0
The Level Set Kalman Filter for State Estimation of Continuous-discrete SystemsCode0
Lossless compression with state space models using bits back codingCode0
Online Joint State Inference and Learning of Partially Unknown State-Space Models—0
Regret-Optimal Filtering for Prediction and EstimationCode0
Method for estimating hidden structures determined by unidentifiable state-space models and time-series data based on the Groebner basis—0
Variational State and Parameter Estimation—0
At the Intersection of Deep Sequential Model Framework and State-space Model Framework: Study on Option Pricing—0
Quantification of mismatch error in randomly switching linear state-space models—0
Variational System Identification for Nonlinear State-Space Models—0
Variational Autoencoders for Learning Nonlinear Dynamics of Physical Systems—0
Normalizing Kalman Filters for Multivariate Time Series Analysis—0
Physics-Informed Neural State Space Models via Learning and Evolution—0
Experimental assessment of polynomial nonlinear state-space and nonlinear-mode models for near-resonant vibrations—0
Generating Series for Networks of Chen-Fliess Series—0
A Systematic Comparison of Forecasting for Gross Domestic Product in an Emergent Economy—0
State space models for building control: how deep should you go?—0
Ensemble Kalman Variational Objectives: Nonlinear Latent Trajectory Inference with A Hybrid of Variational Inference and Ensemble Kalman FilterCode0
Dreaming: Model-based Reinforcement Learning by Latent Imagination without Reconstruction—0
Hierarchical Control of Multi-Agent Systems using Online Reinforcement Learning—0
Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF—0
Stanza: A Nonlinear State Space Model for Probabilistic Inference in Non-Stationary Time Series—0
Neural Physicist: Learning Physical Dynamics from Image Sequences—0
Structured Variational Inference in Partially Observable Unstable Gaussian Process State Space Models—0
Pairs Trading with Nonlinear and Non-Gaussian State Space Models—0
Localized active learning of Gaussian process state space models—0
Active inference on discrete state-spaces: a synthesis—0
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