Alexandros Kalousis

Artificial Intelligence · 2001–2018

A researcher in the Science corpus: 4 papers; trusts 227 researchers and is trusted by 41 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 80 citations into it; #4,957 of 35,345 by trust here, #8,706 by citations
• Computer Vision and Pattern Recognition — 67 citations into it; #4,670 of 21,575 by trust here, #6,954 by citations
• Generative Models — 32 citations into it; #638 of 1,956 by trust here, #1,221 by citations
• Probabilistic & Bayesian Methods — 25 citations into it
• Representation & Self-Supervised Learning — 25 citations into it
• Model Architectures — 15 citations into it
• Optimization & Training — 13 citations into it
• Meta & Continual Learning — 9 citations into it; #271 of 1,041 by trust here, #583 by citations

Whom Alexandros Kalousis trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Alex Krizhevsky
5. Yann LeCun
6. Radford M. Neal
7. L. Eon Bottou
8. Max Welling
9. Ilya Sutskever
10. Kaiming He

Who trusts Alexandros Kalousis overall

1. Fei Ye
2. Vipin Kumar
3. Riccardo Guidotti
4. Rajen Dinesh Shah
5. Girish Chandrashekar
6. Adrian G. Bors
7. Yvan Saeys
8. Sarah Nogueira
9. Bo Liu
10. Rahaf Aljundi

Papers from Alexandros Kalousis's perspective

Ordered by how strongly the researchers Alexandros Kalousis 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. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. GENERATIVE ADVERSARIAL NETS
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Lifelong Generative Modeling (2017) — 134 citations
• Continual Classification Learning Using Generative Models (2018) — 57 citations
• Stability of feature selection algorithms: a study on high-dimensional spaces (2005) — 625 citations
• Estimating the Predictive Accuracy of a Classifier (2001) — 126 citations