SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 26–50 of 2050 papers

TitleStatusHype
LHRS-Bot-Nova: Improved Multimodal Large Language Model for Remote Sensing Vision-Language InterpretationCode2
AD-AGENT: A Multi-agent Framework for End-to-end Anomaly DetectionCode2
Efficient and Effective Time-Series Forecasting with Spiking Neural NetworksCode2
clusterBMA: Bayesian model averaging for clusteringCode1
Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation OverlapCode1
CNN Model & Tuning for Global Road Damage DetectionCode1
abess: A Fast Best Subset Selection Library in Python and RCode1
Change is Hard: A Closer Look at Subpopulation ShiftCode1
Conditional Matrix Flows for Gaussian Graphical ModelsCode1
Can We Characterize Tasks Without Labels or Features?Code1
Cal-SFDA: Source-Free Domain-adaptive Semantic Segmentation with Differentiable Expected Calibration ErrorCode1
Cardea: An Open Automated Machine Learning Framework for Electronic Health RecordsCode1
Brainomaly: Unsupervised Neurologic Disease Detection Utilizing Unannotated T1-weighted Brain MR ImagesCode1
Benchmark Self-Evolving: A Multi-Agent Framework for Dynamic LLM EvaluationCode1
Binary Bleed: Fast Distributed and Parallel Method for Automatic Model SelectionCode1
cegpy: Modelling with Chain Event Graphs in PythonCode1
Convolutional Neural Networks for Classification of Alzheimer's Disease: Overview and Reproducible EvaluationCode1
BarcodeBERT: Transformers for Biodiversity AnalysisCode1
AutoProteinEngine: A Large Language Model Driven Agent Framework for Multimodal AutoML in Protein EngineeringCode1
Bayesian Model Selection of Lithium-Ion Battery Models via Bayesian QuadratureCode1
Automatic Model Selection with Large Language Models for ReasoningCode1
A Concise yet Effective model for Non-Aligned Incomplete Multi-view and Missing Multi-label LearningCode1
BERTScore: Evaluating Text Generation with BERTCode1
BIVDiff: A Training-Free Framework for General-Purpose Video Synthesis via Bridging Image and Video Diffusion ModelsCode1
Automating Outlier Detection via Meta-LearningCode1
Show:102550
← PrevPage 2 of 82Next →

No leaderboard results yet.