Aristidis C. Likas

Artificial Intelligence · 1997–2012

A researcher in the Science corpus: 9 papers; trusts 44 researchers and is trusted by 75 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 17 citations into it; #5,819 of 35,345 by trust here, #10,065 by citations
• Probabilistic & Bayesian Methods — 9 citations into it
• Computer Vision and Pattern Recognition — 8 citations into it; #9,741 of 21,575 by trust here, #14,151 by citations

Whom Aristidis C. Likas trusts overall

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

1. Radford M. Neal
2. Geoffrey E. Hinton
3. Matthew J. Beal
4. Michael I. Jordan
5. Zoubin Ghahramani
6. Lloyd S. Shapley
7. Yann LeCun
8. Yoshua Bengio
9. Nikos A. Vlassis
10. Arthur P. Dempster

Who trusts Aristidis C. Likas overall

1. Dongkun Zhang
2. Jakob Verbeek
3. Pasi Fränti
4. Lu Lu
5. G. Em Karniadakis
6. Jens Berg
7. Volodymyr Melnykov
8. Justin A. Sirignano
9. Stefano Zanero
10. Nikos A. Vlassis

Papers from Aristidis C. Likas's perspective

Ordered by how strongly the researchers Aristidis C. Likas 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• A variational approach for Bayesian blind image deconvolution (2004) — 207 citations
• A spatially constrained mixture model for image segmentation (2005) — 233 citations
• Neural-network methods for boundary value problems with irregular boundaries (2000) — 547 citations
• Kernel-Based Weighted Multi-view Clustering (2012) — 255 citations
• Efficiently Explaining Decisions of Probabilistic RBF Classification Networks (2011) — 10 citations
• The variational approximation for Bayesian inference (2008) — 991 citations
• The global k-means clustering algorithm (2003) — 3,390 citations
• A Greedy EM Algorithm for Gaussian Mixture Learning (2002) — 340 citations
• Artificial neural networks for solving ordinary and partial differential equations (1997)