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Model Selection

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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

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/tranbahien/bae-prior

공식 코드

Model Selection for Bayesian Autoencoders

https://github.com/transfergraph/transfergraph

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Model Selection with Model Zoo via Graph Learning

https://github.com/tsynbio/autope

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AutoProteinEngine: A Large Language Model Driven Agent Framework for Multimodal AutoML in Protein Engineering

https://github.com/tufts-ml/data-emphasized-ELBo

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Learning the Regularization Strength for Deep Fine-Tuning via a Data-Emphasized Variational Objective

https://github.com/tychovdo/lila

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Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations

https://github.com/tychovdo/noethers-razor

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Noether's razor: Learning Conserved Quantities

https://github.com/uchidalab/time-series-transferability

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Model Selection with a Shapelet-based Distance Measure for Multi-source Transfer Learning in Time Series Classification

https://github.com/uclanlp/deepkpg

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Rethinking Model Selection and Decoding for Keyphrase Generation with Pre-trained Sequence-to-Sequence Models

https://github.com/udellgroup/oboe

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OBOE: Collaborative Filtering for AutoML Model Selection

https://github.com/ulab-uiuc/router-r1

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Router-R1: Teaching LLMs Multi-Round Routing and Aggregation via Reinforcement Learning

https://github.com/uoguelph-mlrg/ggm-metrics

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On Evaluation Metrics for Graph Generative Models

https://github.com/ur17/em_mlgssm

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Time Series Clustering with an EM algorithm for Mixtures of Linear Gaussian State Space Models

https://github.com/usaito/counterfactual-cv

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Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models

https://github.com/usc-fortis/ad-agent

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AD-AGENT: A Multi-agent Framework for End-to-end Anomaly Detection

https://github.com/usc-fortis/ad-llm

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AD-LLM: Benchmarking Large Language Models for Anomaly Detection

https://github.com/usc-fortis/nlp-adbench

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NLP-ADBench: NLP Anomaly Detection Benchmark

https://github.com/vanderschaarlab/data-centric-synthetic-data

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Reimagining Synthetic Tabular Data Generation through Data-Centric AI: A Comprehensive Benchmark

https://github.com/vanderschaarlab/data-iq

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Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data

https://github.com/vanderschaarlab/expertise

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Defining Expertise: Applications to Treatment Effect Estimation

https://github.com/vanderschaarlab/hyperimpute

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HyperImpute: Generalized Iterative Imputation with Automatic Model Selection

https://github.com/vanderschaarlab/mlforhealthlabpub

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Synthetic Model Combination: An Instance-wise Approach to Unsupervised Ensemble Learning

https://github.com/vcerqueira/model_selection_forecasting

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Model Selection for Time Series Forecasting: Empirical Analysis of Different Estimators

https://github.com/vdvf96/Differentiable_Model_Selection_for_Ensemble_Learning

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Differentiable Model Selection for Ensemble Learning

https://github.com/victor5as/rieszlearning

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RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests

https://github.com/victoria-klein/learning-lie-group-symmetries

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Learning Lie Group Symmetry Transformations with Neural Networks

https://github.com/vikana/sbic

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Choosing the Number of Topics in LDA Models -- A Monte Carlo Comparison of Selection Criteria

https://github.com/vikranth3140/movie-revenue-prediction

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Movie Revenue Prediction using Machine Learning Models

https://github.com/vimpire00/know2vec1

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Know2Vec: A Black-Box Proxy for Neural Network Retrieval

https://github.com/vingioia90/scm

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Additive Covariance Matrix Models: Modelling Regional Electricity Net-Demand in Great Britain

https://github.com/vishwakarmarhl/rdd2020

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CNN Model & Tuning for Global Road Damage Detection

https://github.com/vital-ultrasound/ai-assisted-echocardiography-for-low-resource-countries

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A Machine Learning Case Study for AI-empowered echocardiography of Intensive Care Unit Patients in low- and middle-income countries

https://github.com/vs-cv/sf-yolo

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Source-Free Domain Adaptation for YOLO Object Detection

https://github.com/wangnanwei/Birth-death-MCMC-Model-Selection

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The scalable Birth-Death MCMC Algorithm for Mixed Graphical Model Learning with Application to Genomic Data Integration

https://github.com/wayne0908/Active-Learning-Homology

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Finding the Homology of Decision Boundaries with Active Learning

https://github.com/weeseml/cvanddoe

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The use of cross validation in the analysis of designed experiments

https://github.com/western-oc2-lab/automl-implementation-for-static-and-dynamic-data-analytics

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IoT Data Analytics in Dynamic Environments: From An Automated Machine Learning Perspective

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