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parameter estimation

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Showing 701–750 of 1719 papers

TitleStatusHype
BSL: An R Package for Efficient Parameter Estimation for Simulation-Based Models via Bayesian Synthetic Likelihood—0
An Evolutionary Algorithm with Crossover and Mutation for Model-Based Clustering—0
Advancing the Understanding of Fine-Grained 3D Forest Structures using Digital Cousins and Simulation-to-Reality: Methods and Datasets—0
Fundamental Limits of Pulse Based UWB ISAC Systems: A Parameter Estimation Perspective—0
A Crucial Parameter for Rank-Frequency Relation in Natural Languages—0
GaitVibe+: Enhancing Structural Vibration-based Footstep Localization Using Temporary Cameras for In-home Gait Analysis—0
Faster-Than-Nyquist Symbol-Level Precoding for Wideband Integrated Sensing and Communications—0
Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning—0
Fast data inversion for high-dimensional dynamical systems from noisy measurements—0
BrowNNe: Brownian Nonlocal Neurons & Activation Functions—0
Gaussian Process Regression for Improved Underwater Navigation—0
Fast Conditional Mixing of MCMC Algorithms for Non-log-concave Distributions—0
Minimax Excess Risk of First-Order Methods for Statistical Learning with Data-Dependent Oracles—0
Generalized Forgetting Recursive Least Squares: Stability and Robustness Guarantees—0
Generalized Gaussian Entropy Model for Point Cloud Attribute Compression with Dynamic Likelihood Intervals—0
Generalized generalized linear models: Convex estimation and online bounds—0
OFDM Reference Signal Pattern Design Criteria for Integrated Communication and Sensing—0
Generalized Time Domain Velocity Vector—0
Fast Cauchy-Rician Modelling of SAR Images with Method of Algebraic Moments Estimator—0
Generative Adversarial Networks for High-Dimensional Item Factor Analysis: A Deep Adversarial Learning Algorithm—0
Generative Learning of Heterogeneous Tail Dependence—0
Brexit Risk Implied by the SABR Martingale Defect in the EUR-GBP Smile—0
Fast Approximate Bayesian Computation for Estimating Parameters in Differential Equations—0
Geometry-Aware Normalizing Wasserstein Flows for Optimal Causal Inference—0
GeometryCrafter: Consistent Geometry Estimation for Open-world Videos with Diffusion Priors—0
Geometry of EM and related iterative algorithms—0
Fast and Scalable Training of Semi-Supervised CRFs with Application to Activity Recognition—0
Globally convergent visual-feature range estimation with biased inertial measurements—0
Global optimization using Gaussian Processes to estimate biological parameters from image data—0
Breaking the T Barrier: Instance-Independent Logarithmic Regret in Stochastic Contextual Linear Bandits—0
An Estimation and Analysis Framework for the Rasch Model—0
Gradient Hard Thresholding Pursuit for Sparsity-Constrained Optimization—0
Advancing Smart Malnutrition Monitoring: A Multi-Modal Learning Approach for Vital Health Parameter Estimation—0
Fast and Reliable Parameter Estimation from Nonlinear Observations—0
Fast and High-Performance Learned Image Compression With Improved Checkerboard Context Model, Deformable Residual Module, and Knowledge Distillation—0
Gridless Parameter Estimation in Partly Calibrated Rectangular Arrays—0
Brain tumor segmentation with missing modalities via latent multi-source correlation representation—0
Fast and Efficient Sequential Radar Parameter Estimation in MIMO-OTFS Systems—0
GWRBoost:A geographically weighted gradient boosting method for explainable quantification of spatially-varying relationships—0
Hard-Clustering with Gaussian Mixture Models—0
Hardness of parameter estimation in graphical models—0
Harnessing Unlabeled Data to Improve Generalization of Biometric Gender and Age Classifiers—0
HeatFormer: A Neural Optimizer for Multiview Human Mesh Recovery—0
Heterogeneous Federated Learning on a Graph—0
Fast and Efficient Estimation of Resonant Modes: A Case Study of Mechanical Drivelines—0
Heterogeneous transfer learning for high dimensional regression with feature mismatch—0
Borrowing Strength in Distributionally Robust Optimization via Hierarchical Dirichlet Processes—0
Hidden Markov models as recurrent neural networks: an application to Alzheimer's disease—0
Hidden Markov models are recurrent neural networks: A disease progression modeling application—0
A Nested Weighted Tchebycheff Multi-Objective Bayesian Optimization Approach for Flexibility of Unknown Utopia Estimation in Expensive Black-box Design Problems—0
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