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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 276–300 of 2050 papers

TitleStatusHype
A Practitioner's Guide to Automatic Kernel Search for Gaussian Processes in Battery Applications—0
Generative diffusion model surrogates for mechanistic agent-based biological models—0
A-DARTS: Stable Model Selection for Data Repair in Time SeriesCode0
Towards Robust and Generalizable Gerchberg Saxton based Physics Inspired Neural Networks for Computer Generated Holography: A Sensitivity Analysis Framework—0
Small or Large? Zero-Shot or Finetuned? Guiding Language Model Choice for Specialized Applications in Healthcare—0
Optimizing Hard Thresholding for Sparse Model Discovery—0
A Novel Parameter-Tying Theorem in Multi-Model Adaptive Systems: Systematic Approach for Efficient Model Selection—0
OpenTCM: A GraphRAG-Empowered LLM-based System for Traditional Chinese Medicine Knowledge Retrieval and Diagnosis—0
Evaluating Meta-Regression Techniques: A Simulation Study on Heterogeneity in Location and Time—0
Topological model selection: a case-study in tumour-induced angiogenesis—0
Transfer Learning via Auxiliary Labels with Application to Cold-Hardiness Prediction—0
Can Pre-training Indicators Reliably Predict Fine-tuning Outcomes of LLMs?—0
Physics-Aware Initialization Refinement in Code-Aided EM for Blind Channel Estimation—0
Meta-Evaluating Local LLMs: Rethinking Performance Metrics for Serious Games—0
Beyond Glucose-Only Assessment: Advancing Nocturnal Hypoglycemia Prediction in Children with Type 1 Diabetes—0
What the HellaSwag? On the Validity of Common-Sense Reasoning BenchmarksCode0
Has the Creativity of Large-Language Models peaked? An analysis of inter- and intra-LLM variability—0
Robust Social Planning—0
Model Selection via MCRB Optimization—0
Quantifying Robustness: A Benchmarking Framework for Deep Learning Forecasting in Cyber-Physical SystemsCode0
Efficient Model Selection for Time Series Forecasting via LLMs—0
Instruction-Guided Autoregressive Neural Network Parameter Generation—0
Optimizing Humor Generation in Large Language Models: Temperature Configurations and Architectural Trade-offs—0
Why risk matters for protein binder design—0
AutoML Algorithms for Online Generalized Additive Model Selection: Application to Electricity Demand Forecasting—0
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