---
title: "Machine Learning 2023 — papers — Elamur Research"
description: "Machine Learning 2023 — papers: 1 paper in the Elamur Research library, with our summaries, ranked by citations."
canonical: "https://research.elamur.ai/free/en/venues/machine-learning/2023/"
---
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[home](https://md.research.elamur.ai/free/en/) / [venues](https://md.research.elamur.ai/free/en/venues/) / [Machine Learning](https://md.research.elamur.ai/free/en/venues/machine-learning/) / 2023

# Machine Learning 2023 — papers

The works of Machine Learning published in 2023 that our library holds (publisher: Springer Science+Business Media): 1 work, listed below with the most cited first; each has a page with our summary, its key points and its references.

[**203** works that year](#all) · [**1** work in our library](https://md.research.elamur.ai/free/en/venues/machine-learning/2023/#works) · [**13** citations of these works](https://md.research.elamur.ai/free/en/venues/machine-learning/2023/#works)

## Most cited papers

By their OpenAlex citations; a paper with our summary links to its page here, the others to the original.

1. **[A theoretical distribution analysis of synthetic minority oversampling technique (SMOTE) for imbalanced learning ↗](https://doi.org/10.1007/s10994-022-06296-4)**Dina Elreedy, Amir F. Atiya, Firuz Kamalov*388 citations*
2. **[Classifier calibration: a survey on how to assess and improve predicted class probabilities ↗](https://doi.org/10.1007/s10994-023-06336-7)**Telmo M. Silva Filho, Hao Song, Miquel Perelló-Nieto et al.*211 citations*
3. **[A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework ↗](https://doi.org/10.1007/s10994-023-06353-6)**Gabriel Aguiar, Bartosz Krawczyk, Alberto Cano*164 citations*
4. **[Domain adversarial neural networks for domain generalization: when it works and how to improve ↗](https://doi.org/10.1007/s10994-023-06324-x)**Anthony Sicilia, Xingchen Zhao, Seong Jae Hwang*134 citations*
5. **[Active learning for data streams: a survey ↗](https://doi.org/10.1007/s10994-023-06454-2)**Davide Cacciarelli, Murat Külahçı*110 citations*
6. **[On the sample complexity of actor-critic method for reinforcement learning with function approximation ↗](https://doi.org/10.1007/s10994-023-06303-2)**Harshat Kumar, Alec Koppel, Alejandro Ribeiro*70 citations*
7. **[Understanding CNN fragility when learning with imbalanced data ↗](https://doi.org/10.1007/s10994-023-06326-9)**Damien A. Dablain, Kristen N. Jacobson, Colin Bellinger et al.*69 citations*
8. **[Fraud detection with natural language processing ↗](https://doi.org/10.1007/s10994-023-06354-5)**Petros Boulieris, John Pavlopoulos, Alexandros Xenos et al.*57 citations*
9. **[Incremental permutation feature importance (iPFI): towards online explanations on data streams ↗](https://doi.org/10.1007/s10994-023-06385-y)**Fabian Fumagalli, Maximilian Muschalik, Eyke Hüllermeier et al.*54 citations*
10. **[Deep reinforcement learning for multi-class imbalanced training: applications in healthcare ↗](https://doi.org/10.1007/s10994-023-06481-z)**Jenny Yang, Rasheed El-Bouri, Odhran O’Donoghue et al.*53 citations*

## All works of the year (203)

The most cited first; 1 with our summary link to their page here, the others to the original.

1. **[A theoretical distribution analysis of synthetic minority oversampling technique (SMOTE) for imbalanced learning ↗](https://doi.org/10.1007/s10994-022-06296-4)**Dina Elreedy, Amir F. Atiya, Firuz Kamalov*388 citations*
2. **[Classifier calibration: a survey on how to assess and improve predicted class probabilities ↗](https://doi.org/10.1007/s10994-023-06336-7)**Telmo M. Silva Filho, Hao Song, Miquel Perelló-Nieto et al.*211 citations*
3. **[A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework ↗](https://doi.org/10.1007/s10994-023-06353-6)**Gabriel Aguiar, Bartosz Krawczyk, Alberto Cano*164 citations*
4. **[Domain adversarial neural networks for domain generalization: when it works and how to improve ↗](https://doi.org/10.1007/s10994-023-06324-x)**Anthony Sicilia, Xingchen Zhao, Seong Jae Hwang*134 citations*
5. **[Active learning for data streams: a survey ↗](https://doi.org/10.1007/s10994-023-06454-2)**Davide Cacciarelli, Murat Külahçı*110 citations*
6. **[On the sample complexity of actor-critic method for reinforcement learning with function approximation ↗](https://doi.org/10.1007/s10994-023-06303-2)**Harshat Kumar, Alec Koppel, Alejandro Ribeiro*70 citations*
7. **[Understanding CNN fragility when learning with imbalanced data ↗](https://doi.org/10.1007/s10994-023-06326-9)**Damien A. Dablain, Kristen N. Jacobson, Colin Bellinger et al.*69 citations*
8. **[Fraud detection with natural language processing ↗](https://doi.org/10.1007/s10994-023-06354-5)**Petros Boulieris, John Pavlopoulos, Alexandros Xenos et al.*57 citations*
9. **[Incremental permutation feature importance (iPFI): towards online explanations on data streams ↗](https://doi.org/10.1007/s10994-023-06385-y)**Fabian Fumagalli, Maximilian Muschalik, Eyke Hüllermeier et al.*54 citations*
10. **[Deep reinforcement learning for multi-class imbalanced training: applications in healthcare ↗](https://doi.org/10.1007/s10994-023-06481-z)**Jenny Yang, Rasheed El-Bouri, Odhran O’Donoghue et al.*53 citations*
11. **[Explainable reinforcement learning (XRL): a systematic literature review and taxonomy ↗](https://doi.org/10.1007/s10994-023-06479-7)**Yanzhe Bekkemoen*51 citations*
12. **[Libsignal: an open library for traffic signal control ↗](https://doi.org/10.1007/s10994-023-06412-y)**Hao Mei, Xiaoliang Lei, Longchao Da et al.*47 citations*
13. **[WEASEL 2.0: a random dilated dictionary transform for fast, accurate and memory constrained time series classification ↗](https://doi.org/10.1007/s10994-023-06395-w)**Patrick Schäfer, Ulf Leser*47 citations*
14. **[Deep learning’s shallow gains: a comparative evaluation of algorithms for automatic music generation ↗](https://doi.org/10.1007/s10994-023-06309-w)**Zongyu Yin, Federico Reuben, Susan Stepney et al.*44 citations*
15. **[Explainable AI in drug discovery: self-interpretable graph neural network for molecular property prediction using concept whitening ↗](https://doi.org/10.1007/s10994-023-06369-y)**Michela Proietti, Alessio Ragno, Biagio La Rosa et al.*44 citations*
16. **[A survey of class-imbalanced semi-supervised learning ↗](https://doi.org/10.1007/s10994-023-06344-7)**Qian Gui, Zhou Hong, Na Guo et al.*43 citations*
17. **[Temporal graph learning for dynamic link prediction with text in online social networks ↗](https://doi.org/10.1007/s10994-023-06475-x)**Manuel Dileo, Matteo Zignani, Sabrina Gaito*38 citations*
18. **[Generation, augmentation, and alignment: a pseudo-source domain based method for source-free domain adaptation ↗](https://doi.org/10.1007/s10994-023-06432-8)**Yuntao Du, Haiyang Yang, Mingcai Chen et al.*37 citations*
19. **[Chinese character recognition with radical-structured stroke trees ↗](https://doi.org/10.1007/s10994-023-06450-6)**Haiyang Yu, Jingye Chen, Bin Li et al.*34 citations*
20. **[Considerations when learning additive explanations for black-box models ↗](https://doi.org/10.1007/s10994-023-06335-8)**Sarah Tan, Giles Hooker, Paul Koch et al.*33 citations*
21. **[Targeted adversarial attacks on wind power forecasts ↗](https://doi.org/10.1007/s10994-023-06396-9)**René Heinrich, Christoph Scholz, Stephan Vogt et al.*32 citations*
22. **[Efficient learning of power grid voltage control strategies via model-based deep reinforcement learning ↗](https://doi.org/10.1007/s10994-023-06422-w)**Ramij Raja Hossain, Tianzhixi Yin, Yan Du et al.*31 citations*
23. **[PreCoF: counterfactual explanations for fairness ↗](https://doi.org/10.1007/s10994-023-06319-8)**Sofie Goethals, David Martens, Toon Calders*31 citations*
24. **[Manas: multi-agent neural architecture search ↗](https://doi.org/10.1007/s10994-023-06379-w)**Vasco Lopes, Fabio Maria Carlucci, Pedro M. Esperança et al.*30 citations*
25. **[Interpreting machine-learning models in transformed feature space with an application to remote-sensing classification ↗](https://doi.org/10.1007/s10994-023-06327-8)**Alexander Brenning*29 citations*

[See all 203 papers in Machine Learning 2023 — papers →](https://md.research.elamur.ai/free/en/venues/machine-learning/2023/papers/)

## Works with our summary in our library (1)

The most cited first (OpenAlex citations plus our library's).

1. **[Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems](https://md.research.elamur.ai/free/en/papers/kramer-2023-automated-scientific-discovery-equation/) [Machine Learning](https://md.research.elamur.ai/free/en/venues/machine-learning/)**Stefan Kramer, Mattia Cerrato, Jannis Brugger, et al.*2023 · 13 citations*

## Fields

[Computer Science (1)](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Materials Science (1)](https://md.research.elamur.ai/free/en/shelves/materials-science/)

## Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

[🧑‍🔬**Ross King**1 work here · 13 citations](https://md.research.elamur.ai/free/en/authors/ross-king/) · [🧑‍🔬**Sašo Džeroski**1 work here · 13 citations](https://md.research.elamur.ai/free/en/authors/saso-dzeroski/)

## Top institutions

Institutions on the bylines of its works here, by the number of works.

[🎓**Johannes Gutenberg University Mainz** Mainz · Germany 1 work here](https://md.research.elamur.ai/free/en/universities/johannes-gutenberg-university-mainz/) · [🎓**University of Cambridge** Cambridge · United Kingdom 1 work here](https://md.research.elamur.ai/free/en/universities/university-of-cambridge/) · [🔬**Jožef Stefan Institute** Ljubljana · Slovenia 1 work here](https://md.research.elamur.ai/free/en/labs/jozef-stefan-institute/) · [🎓**Technische Universität Darmstadt** Darmstadt · Germany 1 work here](https://md.research.elamur.ai/free/en/universities/technische-universitat-darmstadt/) · [🎓**Jožef Stefan International Postgraduate School** Ljubljana · Slovenia 1 work here](https://md.research.elamur.ai/free/en/universities/jozef-stefan-international-postgraduate-school/) · [🔬**Hessian Center for Artificial Intelligence** Darmstadt · Germany 1 work here](https://md.research.elamur.ai/free/en/labs/hessian-center-for-artificial-intelligence/) · [🎓**Chalmers University of Technology** Gothenburg · Sweden 1 work here](https://md.research.elamur.ai/free/en/universities/chalmers-university-of-technology/)

works and citations from OpenAlex and our library.

- [← previous Machine Learning 2000](https://md.research.elamur.ai/free/en/venues/machine-learning/2000/)
- [↑ back to Machine Learning](https://md.research.elamur.ai/free/en/venues/machine-learning/)