Tiago P. Peixoto

Statistical and Nonlinear Physics · 2013–2021

A researcher in the Science corpus: 3 papers; trusts 65 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Statistical and Nonlinear Physics — 63 citations into it; #2,902 of 10,127 by trust here, #5,894 by citations
• Molecular Biology — 27 citations into it
• Computer Networks and Communications — 20 citations into it; #3,810 of 9,886 by trust here, #8,191 by citations
• Artificial Intelligence — 13 citations into it
• Sociology and Political Science — 10 citations into it
• Computational Theory and Mathematics — 7 citations into it
• Computer Vision and Pattern Recognition — 6 citations into it

Whom Tiago P. Peixoto trusts overall

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

1. Mark Newman
2. Santo Fortunato
3. Martin Rosvall
4. Roger Guimerà
5. Aaron Clauset
6. Jorma Rissanen
7. Andrea Lancichinetti
8. Jure Leskovec
9. Hirotugu Akaike
10. Elliott H. Lieb

Who trusts Tiago P. Peixoto overall

1. Santo Fortunato
2. Leto Peel
3. Enkelejda Miho
4. Darko Hric
5. Stephen R. Quake
6. Daniel B. Larremore
7. Rok Roskar
8. Aaron Clauset
9. Victor Greiff
10. Mikko Kivelä

Papers from Tiago P. Peixoto's perspective

Ordered by how strongly the researchers Tiago P. Peixoto trusts endorse each paper. Same corpus, a different order for every researcher.

1. Community structure in social and biological networks (Proceedings of the National Academy of Sciences of the United States of America)
2. Collective dynamics of ‘small-world’ networks
3. The Structure and Function of Complex Networks
4. Statistical mechanics of complex networks
5. Emergence of Scaling in Random Networks
6. ImageNet classification with deep convolutional neural networks
7. Estimating the Dimension of a Model
8. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. Finding and evaluating community structure in networks. (Physical review. E, Statistical, nonlinear, and soft matter physics)

Their papers

• The physics of higher-order interactions in complex systems (2021) — 901 citations
• The graph-tool python library (2014) — 498 citations
• Hierarchical block structures and high-resolution model selection in large networks (2013) — 431 citations