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 1201–1250 of 2050 papers

TitleStatusHype
Forward utilities and Mean-field games under relative performance concerns—0
Foundation of Calculating Normalized Maximum Likelihood for Continuous Probability Models—0
Frame Fusion with Vehicle Motion Prediction for 3D Object Detection—0
From Human Annotation to LLMs: SILICON Annotation Workflow for Management Research—0
From Structured to Unstructured:A Comparative Analysis of Computer Vision and Graph Models in solving Mesh-based PDEs—0
Functional additive models on manifolds of planar shapes and forms—0
Fundamental limits to learning closed-form mathematical models from data—0
Fusion Subspace Clustering for Incomplete Data—0
Fuzzy Fibers: Uncertainty in dMRI Tractography—0
Fast and Accurate Graph Learning for Huge Data via Minipatch Ensembles—0
Gaussian Mixture Clustering Using Relative Tests of Fit—0
Gaussian Process-based Spatial Reconstruction of Electromagnetic fields—0
Gaussian process modeling in approximate Bayesian computation to estimate horizontal gene transfer in bacteria—0
General Bayesian time-varying parameter VARs for predicting government bond yields—0
General Hannan and Quinn Criterion for Common Time Series—0
Generalised Zero-Shot Learning with a Classifier Ensemble over Multi-Modal Embedding Spaces—0
Convergence Rates of Variational Inference in Sparse Deep Learning—0
Generalization error minimization: a new approach to model evaluation and selection with an application to penalized regression—0
Generalized Additive Model Selection—0
Generalized Information Criteria for Structured Sparse Models—0
Generalized Low-Rank Update: Model Parameter Bounds for Low-Rank Training Data Modifications—0
Generalizing Machine Learning Evaluation through the Integration of Shannon Entropy and Rough Set Theory—0
General multi-fidelity surrogate models: Framework and active learning strategies for efficient rare event simulation—0
Generating Automotive Code: Large Language Models for Software Development and Verification in Safety-Critical Systems—0
Generative diffusion model surrogates for mechanistic agent-based biological models—0
Generative Model Selection Using a Scalable and Size-Independent Complex Network Classifier—0
Geometric and Topological Inference for Deep Representations of Complex Networks—0
Global Adaptive Generative Adjustment—0
Global sensitivity analysis informed model reduction and selection applied to a Valsalva maneuver model—0
Going off the Grid: Iterative Model Selection for Biclustered Matrix Completion—0
GPT in Data Science: A Practical Exploration of Model Selection—0
Gradient-based Hyperparameter Optimization without Validation Data for Learning fom Limited Labels—0
Gradient Boosting for Spatial Regression Models with Autoregressive Disturbances—0
Graph-based regularization for regression problems with alignment and highly-correlated designs—0
Graph Coding for Model Selection and Anomaly Detection in Gaussian Graphical Models—0
Graphical LASSO Based Model Selection for Time Series—0
Graph Similarity Description: How Are These Graphs Similar?—0
Graph vs. Sequence: An Empirical Study on Knowledge Forms for Knowledge-Grounded Dialogue—0
GRASMOS: Graph Signage Model Selection for Gene Regulatory Networks—0
Greedy equivalence search for nonparametric graphical models—0
Greedy metrics in orthogonal greedy learning—0
Greedy Model Averaging—0
Green AI in Action: Strategic Model Selection for Ensembles in Production—0
Green Runner: A tool for efficient deep learning component selection—0
Green Runner: A tool for efficient model selection from model repositories—0
GRIDS: Grouped Multiple-Degradation Restoration with Image Degradation Similarity—0
Group-Sparse Model Selection: Hardness and Relaxations—0
Guided Recommendation for Model Fine-Tuning—0
Guided Sampling-based Evolutionary Deep Neural Network for Intelligent Fault Diagnosis—0
GujiBERT and GujiGPT: Construction of Intelligent Information Processing Foundation Language Models for Ancient Texts—0
Show:102550
← PrevPage 25 of 41Next →

No leaderboard results yet.