Entropy | Top Cited Papers Related to Deep Learning and Machine Learning in 2021

1. “Deep Ensemble of Weighted Viterbi Decoders for Tail-Biting Convolutional Codes”
by Tomer Raviv, Asaf Schwartz and Yair Be’ery
Entropy 2021, 23(1), 93; https://doi.org/10.3390/e23010093
Available online: http://www.mdpi.com/1099-4300/23/1/93

2. “Non Stationary Multi-Armed Bandit: Empirical Evaluation of a New Concept Drift-Aware Algorithm”
by Emanuele Cavenaghi, Gabriele Sottocornola, Fabio Stella and Markus Zanker
Entropy 2021, 23(3), 380; https://doi.org/10.3390/e23030380
Available online: http://www.mdpi.com/1099-4300/23/3/380

3. “Getting Ahead of the Arms Race: Hothousing the Coevolution of VirusTotal with a Packer”
by Héctor D. Menéndez, David Clark and Earl T. Barr
Entropy 2021, 23(4), 395; https://doi.org/10.3390/e23040395
Available online: http://www.mdpi.com/1099-4300/23/4/395

4. “Federated Quantum Machine Learning”
by Samuel Yen-Chi Chen and Shinjae Yoo
Entropy 2021, 23(4), 460; https://doi.org/10.3390/e23040460
Available online: http://www.mdpi.com/1099-4300/23/4/460

5. “A Review on Machine Learning Approaches for Network Malicious Behavior Detection in Emerging Technologies”
by Mahdi Rabbani, Yongli Wang, Reza Khoshkangini, Hamed Jelodar, Ruxin Zhao, Sajjad Bagheri Baba Ahmadi and Seyedvalyallah Ayobi
Entropy 2021, 23(5), 529; https://doi.org/10.3390/e23050529
Available online: http://www.mdpi.com/1099-4300/23/5/529

6. “A Hybrid Analysis-Based Approach to Android Malware Family Classification”
by Chao Ding, Nurbol Luktarhan, Bei Lu and Wenhui Zhang
Entropy 2021, 23(8), 1009; https://doi.org/10.3390/e23081009
Available online: http://www.mdpi.com/1099-4300/23/8/1009

7. “Solving Schrödinger Bridges via Maximum Likelihood”
by Francisco Vargas, Pierre Thodoroff, Austen Lamacraft and Neil Lawrence
Entropy 2021, 23(9), 1134; https://doi.org/10.3390/e23091134
Available online: http://www.mdpi.com/1099-4300/23/9/1134

8. “Deep Task-Based Quantization”
by Nir Shlezinger and Yonina C. Eldar
Entropy 2021, 23(1), 104; https://doi.org/10.3390/e23010104
Available online: http://www.mdpi.com/1099-4300/23/1/104

9. “Automatic ECG Classification Using Continuous Wavelet Transform and Convolutional Neural Network”
by Tao Wang, Changhua Lu, Yining Sun, Mei Yang, Chun Liu and Chunsheng Ou
Entropy 2021, 23(1), 119; https://doi.org/10.3390/e23010119
Available online: http://www.mdpi.com/1099-4300/23/1/119

10. “A New Deep Dual Temporal Domain Adaptation Method for Online Detection of Bearings Early Fault”
by Wentao Mao, Bin Sun and Liyun Wang
Entropy 2021, 23(2), 162; https://doi.org/10.3390/e23020162
Available online: http://www.mdpi.com/1099-4300/23/2/162

11. “An Efficient DenseNet-Based Deep Learning Model for Malware Detection”
by Jeyaprakash Hemalatha, S. Abijah Roseline, Subbiah Geetha, Seifedine Kadry and Robertas Damaševičius
Entropy 2021, 23(3), 344; https://doi.org/10.3390/e23030344
Available online: http://www.mdpi.com/1099-4300/23/3/344

12. “A Hybrid Method Based on Extreme Learning Machine and Wavelet Transform Denoising for Stock Prediction”
by Dingming Wu, Xiaolong Wang and Shaocong Wu
Entropy 2021, 23(4), 440; https://doi.org/10.3390/e23040440
Available online: http://www.mdpi.com/1099-4300/23/4/440

13. “Deep Learning Methods for Heart Sounds Classification: A Systematic Review”
by Wei Chen, Qiang Sun, Xiaomin Chen, Gangcai Xie, Huiqun Wu and Chen Xu
Entropy 2021, 23(6), 667; https://doi.org/10.3390/e23060667
Available online: http://www.mdpi.com/1099-4300/23/6/667

14. “Deep Learning for Walking Behaviour Detection in Elderly People Using Smart Footwear”
by Rocío Aznar-Gimeno, Gorka Labata-Lezaun, Ana Adell-Lamora, David Abadía-Gallego, Rafael del-Hoyo-Alonso and Carlos González-Muñoz
Entropy 2021, 23(6), 777; https://doi.org/10.3390/e23060777
Available online: http://www.mdpi.com/1099-4300/23/6/777

15. “Compression Helps Deep Learning in Image Classification”
by En-Hui Yang, Hossam Amer and Yanbing Jiang
Entropy 2021, 23(7), 881; https://doi.org/10.3390/e23070881
Available online: http://www.mdpi.com/1099-4300/23/7/881

16. “Differentiable PAC–Bayes Objectives with Partially Aggregated Neural Networks”
by Felix Biggs and Benjamin Guedj
Entropy 2021, 23(10), 1280; https://doi.org/10.3390/e23101280
Available online: http://www.mdpi.com/1099-4300/23/10/1280

17. “A Lightweight YOLOv4-Based Forestry Pest Detection Method Using Coordinate Attention and Feature Fusion”
by Mingfeng Zha, Wenbin Qian, Wenlong Yi and Jing Hua
Entropy 2021, 23(12), 1587; https://doi.org/10.3390/e23121587
Available online: http://www.mdpi.com/1099-4300/23/12/1587