Model Selection

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 658 papers with code (2,050 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• BERTScore: Evaluating Text Generation with BERT
  21 Apr 2019 20 repositories listed Syntology ran 44 of 76 samples · 32 unverified · 33 pointer-only (licence)
  We propose BERTScore, an automatic evaluation metric for text generation.
• In Search of Lost Domain Generalization
  2 Jul 2020 12 repositories listed Syntology ran 3 of 7 samples · 4 unverified · 1 pointer-only (licence)
  As a first step, we realize that model selection is non-trivial for domain generalization tasks.
• Population Based Training of Neural Networks
  27 Nov 2017 9 repositories listed
  Neural networks dominate the modern machine learning landscape, but their training and success still suffer from sensitivity to empirical choices of hyperparameters such as model architecture, loss function, and…
• Data Splits and Metrics for Method Benchmarking on Surgical Action Triplet Datasets
  11 Apr 2022 8 repositories listed
  We also develop a metrics library, ivtmetrics, for model evaluation on surgical triplets.
• Deep Domain Confusion: Maximizing for Domain Invariance
  10 Dec 2014 7 repositories listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)
  Recent reports suggest that a generic supervised deep CNN model trained on a large-scale dataset reduces, but does not remove, dataset bias on a standard benchmark.
• Laplace Redux -- Effortless Bayesian Deep Learning
  28 Jun 2021 6 repositories listed Syntology ran 1 of 5 samples · 4 unverified · 1 pointer-only (licence)
  Bayesian formulations of deep learning have been shown to have compelling theoretical properties and offer practical functional benefits, such as improved predictive uncertainty quantification and model selection.
• metric-learn: Metric Learning Algorithms in Python
  13 Aug 2019 6 repositories listed
  metric-learn is an open source Python package implementing supervised and weakly-supervised distance metric learning algorithms.
• Conditional Density Estimation Tools in Python and R with Applications to Photometric Redshifts and Likelihood-Free Cosmological Inference
  30 Aug 2019 5 repositories listed Syntology ran 0 of 6 samples · 6 unverified
  We provide sample code in Python and R as well as examples of applications to photometric redshift estimation and likelihood-free cosmological inference via CDE.
• BarcodeBERT: Transformers for Biodiversity Analysis
  4 Nov 2023 4 repositories listed Syntology ran 12 of 16 samples · 4 unverified
  We compared the performance of BarcodeBERT on taxonomic identification tasks against a spectrum of machine learning approaches including supervised training of classical neural architectures and fine-tuning of general…
• Testing Conditional Independence in Supervised Learning Algorithms
  28 Jan 2019 4 repositories listed
  We propose the conditional predictive impact (CPI), a consistent and unbiased estimator of the association between one or several features and a given outcome, conditional on a reduced feature set.
• Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning
  13 Nov 2018 4 repositories listed
  The correct use of model evaluation, model selection, and algorithm selection techniques is vital in academic machine learning research as well as in many industrial settings.
• Variational Bayesian Monte Carlo
  12 Oct 2018 4 repositories listed Syntology ran 3 of 3 samples · 0 unverified
  We introduce here a novel sample-efficient inference framework, Variational Bayesian Monte Carlo (VBMC).
• Tune: A Research Platform for Distributed Model Selection and Training
  13 Jul 2018 4 repositories listed Syntology ran 0 of 9 samples · 9 unverified · 9 pointer-only (licence)
  We show that this interface meets the requirements for a broad range of hyperparameter search algorithms, allows straightforward scaling of search to large clusters, and simplifies algorithm implementation.
• Learning Sparse Neural Networks through L₀ Regularization
  4 Dec 2017 4 repositories listed
  We further propose the \emph{hard concrete} distribution for the gates, which is obtained by "stretching" a binary concrete distribution and then transforming its samples with a hard-sigmoid.
• Neural Vector Spaces for Unsupervised Information Retrieval
  9 Aug 2017 4 repositories listed
  We propose the Neural Vector Space Model (NVSM), a method that learns representations of documents in an unsupervised manner for news article retrieval.
• Encoder vs Decoder: Comparative Analysis of Encoder and Decoder Language Models on Multilingual NLU Tasks
  19 Jun 2024 3 repositories listed Syntology ran 0 of 5 samples · 5 unverified
  This paper explores the performance of encoder and decoder language models on multilingual Natural Language Understanding (NLU) tasks, with a broad focus on Germanic languages.
• The future of cosmological likelihood-based inference: accelerated high-dimensional parameter estimation and model comparison
  21 May 2024 3 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
  First, we demonstrate the application of this paradigm on a simulated cosmic shear analysis for a Stage IV survey in 37- and 39-dimensional parameter spaces, comparing ΛCDM and a dynamical dark energy model…
• A Deep Learning Method for Comparing Bayesian Hierarchical Models
  27 Jan 2023 3 repositories listed
  Bayesian model comparison (BMC) offers a principled approach for assessing the relative merits of competing computational models and propagating uncertainty into model selection decisions.
• LEATHER: A Framework for Learning to Generate Human-like Text in Dialogue
  14 Oct 2022 3 repositories listed
  From this insight, we propose a new algorithm, and empirically, we demonstrate our proposal improves both task-success and human-likeness of the generated text.
• VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition
  19 Jul 2021 3 repositories listed Syntology ran 0 of 6 samples · 6 unverified
  End-to-end AutoML has attracted intensive interests from both academia and industry, which automatically searches for ML pipelines in a space induced by feature engineering, algorithm/model selection, and…
• OTCE: A Transferability Metric for Cross-Domain Cross-Task Representations
  25 Mar 2021 3 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  Specifically, we use optimal transport to estimate domain difference and the optimal coupling between source and target distributions, which is then used to derive the conditional entropy of the target task (task…
• Cardea: An Open Automated Machine Learning Framework for Electronic Health Records
  1 Oct 2020 3 repositories listed
  An estimated 180 papers focusing on deep learning and EHR were published between 2010 and 2018.
• Bayesian Inference of Minimally Complex Models with Interactions of Arbitrary Order
  2 Aug 2020 3 repositories listed
  Finally, because MCMs have interactions of any order, they can reveal the presence of important high-order dependencies in the data, providing a new approach to explore high-order dependencies in complex systems.
• Automatic Catalog of RRLyrae from ∼ 14 million VVV Light Curves: How far can we go with traditional machine-learning?
  1 May 2020 3 repositories listed
  Finally, we show that the use of ensemble classifiers helps resolve the crucial model selection step, and that most errors in the identification of RRLs are related to low quality observations of some sources or to the…
• Deep Learning Algorithms for Rotating Machinery Intelligent Diagnosis: An Open Source Benchmark Study
  6 Mar 2020 3 repositories listed
  Second, we integrate the whole evaluation codes into a code library and release this code library to the public for better development of this field.
• Predictive Multiplicity in Classification
  14 Sep 2019 3 repositories listed
  We apply our tools to measure predictive multiplicity in recidivism prediction problems.
• Interpretable multiclass classification by MDL-based rule lists
  1 May 2019 3 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  Interpretable classifiers have recently witnessed an increase in attention from the data mining community because they are inherently easier to understand and explain than their more complex counterparts.
• Forecasting with time series imaging
  17 Apr 2019 3 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  Recently, the use of time series features for forecast model averaging has been an emerging research focus in the forecasting community.
• Automatic Gradient Boosting
  10 Jul 2018 3 repositories listed
  Automatic machine learning performs predictive modeling with high performing machine learning tools without human interference.
• A comparison of methods for model selection when estimating individual treatment effects
  14 Apr 2018 3 repositories listed Syntology ran 0 of 6 samples · 6 unverified
  Instead of relying on a single method, multiple models fit by a diverse set of algorithms should be evaluated against each other using an objective function learned from the validation set.

Syntology lines on 15 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.