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State Space Models

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Showing 601–650 of 923 papers

TitleStatusHype
Accelerating Toeplitz Neural Network with Constant-time Inference ComplexityCode1
Generative learning for nonlinear dynamics—0
Convolutional State Space Models for Long-Range Spatiotemporal ModelingCode1
Laughing Hyena Distillery: Extracting Compact Recurrences From ConvolutionsCode2
An adaptive ensemble filter for heavy-tailed distributions: tuning-free inflation and localizationCode0
S4Sleep: Elucidating the design space of deep-learning-based sleep stage classification modelsCode1
Never Train from Scratch: Fair Comparison of Long-Sequence Models Requires Data-Driven PriorsCode1
Robustifying State-space Models for Long Sequences via Approximate Diagonalization—0
Scaling Representation Learning from Ubiquitous ECG with State-Space ModelsCode1
State-space Models with Layer-wise Nonlinearity are Universal Approximators with Exponential Decaying MemoryCode1
Reachability Analysis of ARMAX Models—0
Sampling-Free Probabilistic Deep State-Space Models—0
Out of Distribution Detection via Domain-Informed Gaussian Process State Space Models—0
Relative representations for cognitive graphsCode0
Spiking Structured State Space Model for Monaural Speech Enhancement—0
A study on fault diagnosis in nonlinear dynamic systems with uncertainties—0
Towards Efficient Modeling and Inference in Multi-Dimensional Gaussian Process State-Space ModelsCode1
Towards quantitative precision for ECG analysis: Leveraging state space models, self-supervision and patient metadataCode1
Multi-Response Heteroscedastic Gaussian Process Models and Their Inference—0
Stabilizing RNN Gradients through Pre-training—0
Universality of Linear Recurrences Followed by Non-linear Projections: Finite-Width Guarantees and Benefits of Complex Eigenvalues—0
Graphs in State-Space Models for Granger Causality in Climate Science—0
Meta-State-Space Learning: An Identification Approach for Stochastic Dynamical SystemsCode0
Sparse Graphical Linear Dynamical Systems—0
Structured State Space Models for Multiple Instance Learning in Digital PathologyCode1
Why are state-space models more expressive than n-gram models?—0
Sparse Modular Activation for Efficient Sequence ModelingCode1
Block-State Transformers—0
A Recursive Newton Method for Smoothing in Nonlinear State Space Models—0
Deep Gaussian Markov Random Fields for Graph-Structured Dynamical Systems—0
A Quantitative Review on Language Model Efficiency Research—0
A Neural State-Space Model Approach to Efficient Speech SeparationCode1
Multi-Head State Space Model for Speech Recognition—0
Variational Nonlinear Kalman Filtering with Unknown Process Noise Covariance—0
Cheap and Deterministic Inference for Deep State-Space Models of Interacting Dynamical SystemsCode0
Posterior Sampling for Deep Reinforcement LearningCode1
Neural State-Space Models: Empirical Evaluation of Uncertainty QuantificationCode0
Initialization Approach for Nonlinear State-Space Identification via the Subspace Encoder Approach—0
Learning Stable and Robust Linear Parameter-Varying State-Space Models—0
Computationally efficient predictive control based on ANN state-space models—0
Maximum likelihood smoothing estimation in state-space models: An incomplete-information based approach—0
Inverse Cubature and Quadrature Kalman filters—0
Effectively Modeling Time Series with Simple Discrete State SpacesCode1
Variational Gaussian filtering via Wasserstein gradient flowsCode0
Resurrecting Recurrent Neural Networks for Long SequencesCode1
Structured State Space Models for In-Context Reinforcement LearningCode1
Time series anomaly detection with reconstruction-based state-space modelsCode0
Fast Randomized Subspace System Identification for Large I/O Data—0
PlaNet-ClothPick: Effective Fabric Flattening Based on Latent Dynamic Planning—0
Auxiliary MCMC and particle Gibbs samplers for parallelisable inference in latent dynamical systemsCode0
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