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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 51–75 of 2050 papers

TitleStatusHype
A Concise yet Effective model for Non-Aligned Incomplete Multi-view and Missing Multi-label LearningCode1
Cardea: An Open Automated Machine Learning Framework for Electronic Health RecordsCode1
Deep Learning Algorithms for Rotating Machinery Intelligent Diagnosis: An Open Source Benchmark StudyCode1
Deep learning for dynamic graphs: models and benchmarksCode1
Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation OverlapCode1
abess: A Fast Best Subset Selection Library in Python and RCode1
DisastIR: A Comprehensive Information Retrieval Benchmark for Disaster ManagementCode1
Distributed Out-of-Memory NMF on CPU/GPU ArchitecturesCode1
A General Model for Aggregating Annotations Across Simple, Complex, and Multi-Object Annotation TasksCode1
Brainomaly: Unsupervised Neurologic Disease Detection Utilizing Unannotated T1-weighted Brain MR ImagesCode1
BIVDiff: A Training-Free Framework for General-Purpose Video Synthesis via Bridging Image and Video Diffusion ModelsCode1
Empirical evaluation of scoring functions for Bayesian network model selectionCode1
A comparison of methods for model selection when estimating individual treatment effectsCode1
Adversarial Branch Architecture Search for Unsupervised Domain AdaptationCode1
Binary Bleed: Fast Distributed and Parallel Method for Automatic Model SelectionCode1
Cal-SFDA: Source-Free Domain-adaptive Semantic Segmentation with Differentiable Expected Calibration ErrorCode1
clusterBMA: Bayesian model averaging for clusteringCode1
BayesOpt Adversarial AttackCode1
Bayesian Model Selection, the Marginal Likelihood, and GeneralizationCode1
Benchmarking the Performance of Bayesian Optimization across Multiple Experimental Materials Science DomainsCode1
Additive Covariance Matrix Models: Modelling Regional Electricity Net-Demand in Great BritainCode1
AutoProteinEngine: A Large Language Model Driven Agent Framework for Multimodal AutoML in Protein EngineeringCode1
BarcodeBERT: Transformers for Biodiversity AnalysisCode1
Automatic Model Selection with Large Language Models for ReasoningCode1
AD-LLM: Benchmarking Large Language Models for Anomaly DetectionCode1
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