Anna L. Buczak

Artificial Intelligence · 2016–2019

A researcher in the Science corpus: 2 papers; trusts 84 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 75 citations into it; #11,181 of 35,345 by trust here, #13,962 by citations
• Computer Networks and Communications — 55 citations into it; #2,268 of 9,886 by trust here, #2,613 by citations
• Signal Processing — 38 citations into it; #2,033 of 7,572 by trust here, #2,114 by citations
• Computer Vision and Pattern Recognition — 25 citations into it
• Model Architectures — 18 citations into it
• Information Systems — 13 citations into it
• Natural Language Processing — 12 citations into it
• Representation & Self-Supervised Learning — 8 citations into it

Whom Anna L. Buczak trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Geoffrey E. Hinton
2. Yann LeCun
3. Vladimir Naumovich Vapni
4. Teuvo Kohonen
5. J. Ross Quinlan
6. Muthu Dayalan
7. Ian T. Jolliffe
8. James Cannady
9. Yoshua Bengio
10. Yoav Freund

Who trusts Anna L. Buczak overall

1. Paulo Angelo Alves Resende
2. Ansam Khraisat
3. Syeda Manjia Tahsien
4. Mohamed Amine Ferrag
5. Liang Xiao
6. André Costa Drummond
7. Hadis Karimipour
8. Leandros A. Maglaras
9. Thanh Thi Nguyen
10. Iqbal Gondal

Papers from Anna L. Buczak's perspective

Ordered by how strongly the researchers Anna L. Buczak trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• A Survey of Deep Learning Methods for Cyber Security (2019) — 510 citations
• A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection (2016) — 1,128 citations