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Model Selection

Given a set of candidate models, the goal of Model Selection is to select the model that best approximates the observed data and captures its underlying regularities. Model Selection criteria are defined such that they strike a balance between the goodness of fit, and the generalizability or complexity of the models.

Source: Kernel-based Information Criterion

Papers

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Showing 76–100 of 2050 papers

TitleStatusHype
Bayesian Model Selection of Lithium-Ion Battery Models via Bayesian QuadratureCode1
BIVDiff: A Training-Free Framework for General-Purpose Video Synthesis via Bridging Image and Video Diffusion ModelsCode1
A Data-Centric Perspective on Evaluating Machine Learning Models for Tabular DataCode1
Additive Covariance Matrix Models: Modelling Regional Electricity Net-Demand in Great BritainCode1
Cardea: An Open Automated Machine Learning Framework for Electronic Health RecordsCode1
A comparison of methods for model selection when estimating individual treatment effectsCode1
BayesOpt Adversarial AttackCode1
clusterBMA: Bayesian model averaging for clusteringCode1
AD-LLM: Benchmarking Large Language Models for Anomaly DetectionCode1
Conditional Matrix Flows for Gaussian Graphical ModelsCode1
Convolutional Neural Networks for Classification of Alzheimer's Disease: Overview and Reproducible EvaluationCode1
AutoProteinEngine: A Large Language Model Driven Agent Framework for Multimodal AutoML in Protein EngineeringCode1
A Concise yet Effective model for Non-Aligned Incomplete Multi-view and Missing Multi-label LearningCode1
Automating Outlier Detection via Meta-LearningCode1
Data thinning for convolution-closed distributionsCode1
Deep Learning Algorithms for Rotating Machinery Intelligent Diagnosis: An Open Source Benchmark StudyCode1
A General Model for Aggregating Annotations Across Simple, Complex, and Multi-Object Annotation TasksCode1
Deep Reinforcement Model Selection for Communications Resource Allocation in On-Site Medical CareCode1
DEGAN: Time Series Anomaly Detection using Generative Adversarial Network Discriminators and Density EstimationCode1
BarcodeBERT: Transformers for Biodiversity AnalysisCode1
Benchmarking the Performance of Bayesian Optimization across Multiple Experimental Materials Science DomainsCode1
Cal-SFDA: Source-Free Domain-adaptive Semantic Segmentation with Differentiable Expected Calibration ErrorCode1
Empirical evaluation of scoring functions for Bayesian network model selectionCode1
Entropic Descent Archetypal Analysis for Blind Hyperspectral UnmixingCode1
A Survey and Implementation of Performance Metrics for Self-Organized MapsCode1
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