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Top 25 Machine Learning Papers 2020

The most-cited papers published in 2020 on the topic of machine learning

Despite everything that occurred in the world this year, we still had the privilege to see some truly incredible research, particularly in the area of machine learning. This year, a number of significant issues—such as ethical issues, important prejudices, and much more—were highlighted. Machine Learning is constantly developing, and its relationship to our understanding of the human brain and its potential applications are also exciting. In case you missed any of them, here are the best machine learning research papers of the year 2020.
DOI: 10.1016/j.inffus.2019.12.012
2020
Cited 1,397 times
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI
Alejandro Barredo Arrieta, Natalia Díaz-Rodríguez, Javier Del Ser, Adrien Bennetot, Siham Tabik, Alberto Barbado, Salvador García, Sergio Gil-Lopez, Daniel Molina, Richard Benjamins, Raja Chatila, Francisco Herrera
Artificial intelligence
Computer science
Taxonomy (biology)
DOI: 10.1038/s41586-019-1923-7
2020
Cited 1,117 times
Improved protein structure prediction using potentials from deep learning
Andrew W. Senior, Richard Evans, John M. Jumper, James Kirkpatrick, Laurent Sifre, Tim Green, Chongli Qin, Augustin Žídek, Alexander Nelson, Alex Bridgland, Hugo Penedones, Stig Petersen, Karen Simonyan, Steve Crossan, Pushmeet Kohli, David T. Jones, David Silver, Koray Kavukcuoglu, Demis Hassabis
Machine learning
Computational biology
Pattern recognition (psychology)
DOI: 10.1016/j.compbiomed.2020.103792
2020
Cited 1,034 times
Automated detection of COVID-19 cases using deep neural networks with X-ray images.
Tülin Öztürk, Muhammed Talo, Eylul Azra Yildirim, Ulas Baran Baloglu, Ozal Yildirim, U. Rajendra Acharya
Computer science
Coronavirus disease 2019 (COVID-19)
Artificial intelligence
DOI: 10.1186/s12864-019-6413-7
2020
Cited 921 times
The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation
Davide Chicco, Giuseppe Jurman
Binary classification
False positive paradox
False positives and false negatives
DOI: 10.1007/s13246-020-00865-4
2020
Cited 905 times
Covid-19: automatic detection from X-ray images utilizing transfer learning with convolutional neural networks.
Ioannis D. Apostolopoulos, Tzani A. Mpesiana
Pattern recognition (psychology)
Artificial neural network
Machine learning
DOI: 10.1007/s11263-019-01247-4
2020
Cited 861 times
Deep Learning for Generic Object Detection: A Survey
Li Liu, Wanli Ouyang, Xiaogang Wang, Paul Fieguth, Jie Chen, Xinwang Liu, Matti Pietikäinen
Computer science
Object detection
Artificial intelligence
DOI: 10.1007/s10462-020-09825-6
2020
Cited 692 times
A survey of the recent architectures of deep convolutional neural networks
Asifullah Khan, Anabia Sohail, Umme Zahoora, Aqsa Saeed Qureshi
Computer science
Convolutional neural network
Deep learning
DOI: 10.1162/tacl_a_00300
2020
Cited 683 times
SpanBERT: Improving Pre-training by Representing and Predicting Spans
Mandar Joshi, Danqi Chen, Yinhan Liu, Daniel S. Weld, Luke Zettlemoyer, Omer Levy
Computer science
Security token
Training (meteorology)
DOI: 10.1016/j.physd.2019.132306
2020
Cited 640 times
Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) Network
Alex Sherstinsky
Recurrent neural network
Computer science
Inference
DOI: 10.1007/s10044-021-00984-y
2020
Cited 474 times
Automatic Detection of Coronavirus Disease (COVID-19) Using X-ray Images and Deep Convolutional Neural Networks
Ali Narin, Ceren Kaya, Ziynet Pamuk
Deep learning
2019-20 coronavirus outbreak
Pattern recognition (psychology)
DOI: 10.1016/j.neunet.2019.08.025
2020
Cited 470 times
MultiResUNet : Rethinking the U-Net architecture for multimodal biomedical image segmentation.
Nabil Ibtehaz, M. Sohel Rahman
Architecture
Computer science
Artificial intelligence
DOI: 10.1038/s42256-020-0180-7
2020
Cited 462 times
An interpretable mortality prediction model for COVID-19 patients
Li Yan, Hai-Tao Zhang, Jorge Goncalves, Yang Xiao, Maolin Wang, Yuqi Guo, Chuan Sun, Xiuchuan Tang, Jing Liang, Mingyang Zhang, Xiang Huang, Ying Xiao, Haosen Cao, Yanyan Chen, Tongxin Ren, Fang Wang, Yaru Xiao, Sufang Huang, Xi Tan, Niannian Huang, Bo Jiao, Cheng Cheng, Yong Zhang, Ailin Luo, Laurent Mombaerts, Junyang Jin, Zhiguo Cao, Shusheng Li, Hui Xu, Ye Yuan
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
2019-20 coronavirus outbreak
Computer science
DOI: 10.1038/s41586-020-03051-4
2020
Cited 440 times
Mastering Atari, Go, chess and shogi by planning with a learned model
Julian Schrittwieser, Ioannis Antonoglou, Thomas Hubert, Karen Simonyan, Laurent Sifre, Simon Schmitt, Arthur Guez, Edward Lockhart, Demis Hassabis, Thore Graepel, Timothy P. Lillicrap, David Silver
Computer science
Reinforcement learning
Artificial intelligence
DOI: 10.1007/s10994-019-05855-6
2020
Cited 435 times
A survey on semi-supervised learning
Jesper E. van Engelen, Holger H. Hoos
Artificial intelligence
Machine learning
Computer science
DOI: 10.1162/tacl_a_00343
2020
Cited 404 times
Multilingual Denoising Pre-training for Neural Machine Translation
Yinhan Liu, Jiatao Gu, Naman Goyal, Xian Li, Sergey Edunov, Marjan Ghazvininejad, Michael Lewis, Luke Zettlemoyer
Artificial intelligence
Training (meteorology)
Natural language processing
DOI: 10.1109/tkde.2020.2981333
2020
Cited 376 times
Deep Learning on Graphs: A Survey
Ziwei Zhang, Peng Cui, Wenwu Zhu
Computer science
Deep learning
Artificial intelligence
DOI: 10.1016/j.chaos.2020.109864
2020
Cited 372 times
Time Series Forecasting of COVID-19 transmission in Canada Using LSTM Networks.
Vinay Kumar Reddy Chimmula, Lei Zhang
Computer science
Autoregressive integrated moving average
Series (stratigraphy)
DOI: 10.1016/j.media.2020.101794
2020
Cited 351 times
Deep-COVID: Predicting COVID-19 from chest X-ray images using deep transfer learning.
Shervin Minaee, Rahele Kafieh, Milan Sonka, Shakib Yazdani, Ghazaleh Jamalipour Soufi
Computer science
Convolutional neural network
Machine learning
DOI: 10.1016/j.ijforecast.2019.07.001
2020
Cited 347 times
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
Valentin Flunkert, David Salinas, Jan Gasthaus
Probabilistic forecasting
Probabilistic logic
Autoregressive model
DOI: 10.1109/comst.2020.2970550
2020
Cited 335 times
Convergence of Edge Computing and Deep Learning: A Comprehensive Survey
Xiaofei Wang, Yiwen Han, Victor C. M. Leung, Dusit Niyato, Xueqiang Yan, Xu Chen
Artificial neural network
Convergence (economics)
Enhanced Data Rates for GSM Evolution
DOI: 10.1609/aaai.v34i07.6999
2020
Cited 328 times
Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression
Zhaohui Zheng, Ping Wang, Wei Liu, Jinze Li, Rongguang Ye, Dongwei Ren
Bounding overwatch
Artificial intelligence
Machine learning
DOI: 10.1016/j.compbiomed.2020.103795
2020
Cited 326 times
Application of deep learning technique to manage COVID-19 in routine clinical practice using CT images: Results of 10 convolutional neural networks.
Ali Abbasian Ardakani, Alireza Rajabzadeh Kanafi, U. Rajendra Acharya, Nazanin Khadem, Afshin Mohammadi
Computer science
Artificial intelligence
Artificial neural network
DOI: 10.1109/tits.2019.2935152
2020
Cited 311 times
T-GCN: A Temporal Graph Convolutional Network for Traffic Prediction
Ling Zhao, Yujiao Song, Chao Zhang, Yu Liu, Pu Wang, Tao Lin, Min Deng, Haifeng Li
Convolutional neural network
Artificial intelligence
Graph
DOI: 10.1109/tnnls.2019.2944481
2020
Cited 308 times
Robust and Communication-Efficient Federated Learning From Non-i.i.d. Data
Felix Sattler, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek
Federated learning
Differential privacy
Machine learning
DOI: 10.1109/tbdata.2018.2850013
2020
Cited 306 times
Network Representation Learning: A Survey
Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang
Computer science
Feature learning
Machine learning