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State Space Models

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Showing 701–750 of 923 papers

TitleStatusHype
How to Train Your HiPPO: State Space Models with Generalized Orthogonal Basis Projections—0
On the Parameterization and Initialization of Diagonal State Space Models—0
SIXO: Smoothing Inference with Twisted ObjectivesCode0
GD-VAEs: Geometric Dynamic Variational Autoencoders for Learning Nonlinear Dynamics and Dimension ReductionsCode1
Improving the Diagnosis of Psychiatric Disorders with Self-Supervised Graph State Space Models—0
Amortized backward variational inference in nonlinear state-space models—0
Counterfactual Analysis in Dynamic Latent State Models—0
Deep Direct Discriminative Decoders for High-dimensional Time-series Data AnalysisCode0
Learning Individual Interactions from Population Dynamics with Discrete-Event Simulation Model—0
Continuous-time identification of dynamic state-space models by deep subspace encodingCode0
Learning Reduced Nonlinear State-Space Models: an Output-Error Based Canonical Approach—0
On the Herdability of Linear Time-Invariant Systems with Special Topological Structures—0
A Tutorial on Solution Properties of State Space Models of Dynamical Systems—0
Causal Discovery of Macroeconomic State-Space ModelsCode0
Impedance-based Root-cause Analysis: Comparative Study of Impedance Models and Calculation of Eigenvalue Sensitivity—0
Inverse Online Learning: Understanding Non-Stationary and Reactionary PoliciesCode0
Interpretable Latent Variables in Deep State Space Models—0
Neural Ordinary Differential Equations for Nonlinear System Identification—0
Conditional Simulation Using Diffusion Schrödinger BridgesCode1
It's Raw! Audio Generation with State-Space ModelsCode1
Data-driven approximation and reduction from noisy data in matrix pencil frameworks—0
Simple Models and Biased Forecasts—0
Efficient learning of hidden state LTI state space models of unknown order—0
Inertial Navigation Using an Inertial Sensor ArrayCode0
The Annotated S4—0
Inverse Extended Kalman Filter -- Part I: Fundamentals—0
Linear Variational State-Space FilteringCode0
Variational-Based Nonlinear Bayesian Filtering with Biased Observations—0
Reactive Message Passing for Scalable Bayesian InferenceCode1
Efficient Estimation of State-Space Mixed-Frequency VARs: A Precision-Based Approach—0
SSDNet: State Space Decomposition Neural Network for Time Series ForecastingCode0
On Recursive State Estimation for Linear State-Space Models Having Quantized Output Data—0
Traversing Time with Multi-Resolution Gaussian Process State-Space Models—0
Robust Robotic Control from Pixels using Contrastive Recurrent State-Space ModelsCode1
Probabilistic Transformer For Time Series Analysis—0
Latent Matters: Learning Deep State-Space Models—0
Efficient Learning of the Parameters of Non-Linear Models using Differentiable Resampling in Particle Filters—0
Bayes-Newton Methods for Approximate Bayesian Inference with PSD GuaranteesCode1
Likelihood-Free Inference in State-Space Models with Unknown DynamicsCode0
Explicit Port-Hamiltonian FEM-Models for Linear Mechanical Systems with Non-Uniform Boundary Conditions—0
Online Variational Filtering and Parameter LearningCode1
Iterated Block Particle Filter for High-dimensional Parameter Learning: Beating the Curse of Dimensionality—0
Physics-guided Deep Markov Models for Learning Nonlinear Dynamical Systems with UncertaintyCode1
Uncertainty in Data-Driven Kalman Filtering for Partially Known State-Space ModelsCode1
RTSNet: Learning to Smooth in Partially Known State-Space Models (Preprint)Code1
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
Representation learning for neural population activity with Neural Data TransformersCode1
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