Phillip Verbancsics

Artificial Intelligence · 2013–2015

A researcher in the Science corpus: 2 papers; trusts 14 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 13 citations into it; #9,935 of 35,345 by trust here, #25,040 by citations
• Computer Vision and Pattern Recognition — 7 citations into it

Whom Phillip Verbancsics trusts overall

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

1. Kenneth O. Stanley
2. Geoffrey E. Hinton
3. Ruslan Salakhutdinov
4. Risto Miikkulainen
5. Yann LeCun
6. Yoshua Bengio
7. Alex Krizhevsky
8. Jason Gauci
9. L. Eon Bottou
10. Ilya Sutskever

Who trusts Phillip Verbancsics overall

1. Bowen Baker
2. Masanori Suganuma
3. Otkrist Gupta
4. Tal Ben-Nun
5. Shinichi Shirakawa
6. Ramesh Raskar
7. Nikhil Naik
8. Chrisantha Fernando
9. Tomoharu Nagao
10. Torsten Hoefler

Papers from Phillip Verbancsics's perspective

Ordered by how strongly the researchers Phillip Verbancsics 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
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. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Generative NeuroEvolution for Deep Learning (2013) — 54 citations
• Image Classification Using Generative Neuro Evolution for Deep Learning (2015) — 48 citations