Bruno Ribeiro
Artificial Intelligence · 2010–2019
A researcher in the Science corpus: 5 papers; trusts 105 researchers and is trusted by 13 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 88 citations into it; #12,363 of 35,345 by trust here, #14,438 by citations
- Graph Learning — 66 citations into it
- Computer Vision and Pattern Recognition — 39 citations into it
- Statistical and Nonlinear Physics — 29 citations into it
- Representation & Self-Supervised Learning — 28 citations into it
- Model Architectures — 23 citations into it
- Molecular Biology — 23 citations into it; #14,500 of 17,773 by trust here, #12,465 by citations
- Computer Networks and Communications — 19 citations into it
Whom Bruno Ribeiro trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Mark Newman
- Diederik P. Kingma
- Geoffrey E. Hinton
- Jure Leskovec
- Yoshua Bengio
- Yann LeCun
- Ilya Sutskever
- L. Eon Bottou
- Sean P. Meyn
- Alex Krizhevsky
Who trusts Bruno Ribeiro overall
Papers from Bruno Ribeiro's perspective
Ordered by how strongly the researchers Bruno Ribeiro trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Relational Pooling for Graph Representations (2019) — 285 citations
- Janossy Pooling: Learning Deep Permutation-Invariant Functions for Variable-Size Inputs (2018) — 214 citations
- Estimating and sampling graphs with multidimensional random walks (2010) — 367 citations
- Oboe: auto-tuning video ABR algorithms to network conditions (2018) — 353 citations
- On the Equivalence between Positional Node Embeddings and Structural Graph Representations (2019) — 143 citations