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State Space Models

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Showing 751–800 of 923 papers

TitleStatusHype
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
Model-Based Reinforcement Learning via Latent-Space CollocationCode1
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
Smoothing-Averse Control: Covertness and Privacy from Smoothers—0
PAC-Bayesian theory for stochastic LTI systems—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
Differentiable Particle Filtering via Entropy-Regularized Optimal TransportCode1
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
At the Intersection of Deep Sequential Model Framework and State-space Model Framework: Study on Option Pricing—0
Variational State and Parameter Estimation—0
Variational System Identification for Nonlinear State-Space Models—0
Quantification of mismatch error in randomly switching linear 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
Dynamical Variational Autoencoders: A Comprehensive ReviewCode1
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
Continuous-time system identification with neural networks: Model structures and fitting criteriaCode1
Pairs Trading with Nonlinear and Non-Gaussian State Space Models—0
Localized active learning of Gaussian process state space models—0
The Discriminative Kalman Filter for Bayesian Filtering with Nonlinear and Nongaussian Observation ModelsCode1
Deep State Space Models for Nonlinear System IdentificationCode1
Active inference on discrete state-spaces: a synthesis—0
Learning Driver Behaviors Using A Gaussian Process Augmented State-Space Model—0
Linear-time inference for Gaussian Processes on one dimension—0
Data-driven switching logic design for switched linear systems—0
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