Nicolas Macris

Computational Mechanics · 2017–2019

A researcher in the Science corpus: 4 papers; trusts 24 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Computational Mechanics — 20 citations into it
• Artificial Intelligence — 15 citations into it; #26,264 of 35,345 by trust here, #22,463 by citations
• Computer Networks and Communications — 15 citations into it
• Signal Processing — 15 citations into it
• Statistics and Probability — 14 citations into it; #8,625 of 12,932 by trust here, #10,275 by citations
• Condensed Matter Physics — 11 citations into it; #995 of 1,948 by trust here, #1,770 by citations
• Electrical and Electronic Engineering — 7 citations into it
• Mathematical Physics — 7 citations into it

Whom Nicolas Macris trusts overall

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

1. Michel Talagrand
2. David L. Donoho
3. Francesco Guerra
4. Gábor Lugosi
5. Jean Barbier
6. Mohsen Bayati
7. Iain M. Johnstone
8. Andrea Montanari
9. Dongning Guo
10. M. M'ezard

Who trusts Nicolas Macris overall

1. Jean Barbier
2. Benjamin Aubin
3. Stefano Spigler

Papers from Nicolas Macris's perspective

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

1. The dynamics of message passing on dense graphs, with applications to compressed sensing
2. Solution of 'Solvable model of a spin glass'
3. Understanding deep learning requires rethinking generalization
4. Message-passing algorithms for compressed sensing
5. Deep Learning
6. Statistical learning theory
7. Spin glasses : a challenge for mathematicians : cavity and mean field models
8. Et al
9. Modern Coding Theory
10. Observed universality of phase transitions in high-dimensional geometry, with implications for modern data analysis and signal processing (Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences)

Their papers

• The committee machine: computational to statistical gaps in learning a two-layers neural network (2018) — 123 citations
• The adaptive interpolation method: a simple scheme to prove replica formulas in Bayesian inference (2018) — 143 citations
• 0-1 Phase Transitions in Sparse Spiked Matrix Estimation (2019) — 15 citations
• Optimal errors and phase transitions in high-dimensional generalized linear models (2017) — 314 citations