Facundo M'emoli
Computer Vision and Pattern Recognition · 2005–2021
A researcher in the Science corpus: 7 papers; trusts 116 researchers and is trusted by 64 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 45 citations into it; #3,366 of 21,575 by trust here, #6,671 by citations
- Computational Mechanics — 33 citations into it; #454 of 10,001 by trust here, #1,745 by citations
- Computational Theory and Mathematics — 20 citations into it; #2,572 of 12,182 by trust here, #5,239 by citations
- Applied Mathematics — 15 citations into it
- Computer Graphics and Computer-Aided Design — 15 citations into it; #994 of 1,584 by trust here, #843 by citations
- Geometry and Topology — 15 citations into it; #1,456 of 7,422 by trust here, #2,475 by citations
- Representation & Self-Supervised Learning — 11 citations into it; #2,338 of 3,145 by trust here, #3,089 by citations
- Mathematical Physics — 8 citations into it
Whom Facundo M'emoli trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Misha Gromov
- Karl‐Theodor Sturm
- Cédric Villani
- Ronald R. Coifman
- Bruno Lévy
- Raif M. Rustamov
- Stéphane Lafon
- A. Bronstein
- Laurent Younes
- Johan Efberg
Who trusts Facundo M'emoli overall
- Matthias Vestner
- Emanuele Rodolà
- A. Bronstein
- Davide Boscaini
- Roee Litman
- G. Peyr'e
- Michael M. Bronstein
- Yaron Lipman
- Jonathan Masci
- Valentin De Bortoli
Papers from Facundo M'emoli's perspective
Ordered by how strongly the researchers Facundo M'emoli trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- One Point Isometric Matching with the Heat Kernel (2010) — 361 citations
- A Theoretical and Computational Framework for Isometry Invariant Recognition of Point Cloud Data (2005) — 351 citations
- Gromov–Wasserstein Distances and the Metric Approach to Object Matching (2011) — 783 citations
- Topological Methods for the Analysis of High Dimensional Data Sets and 3D Object Recognition (2007) — 751 citations
- A spectral notion of Gromov–Wasserstein distance and related methods (2011) — 66 citations
- Classifying Clustering Schemes (2010) — 98 citations
- The Gromov–Hausdorff distance between spheres (2021) — 47 citations