Carla P. Gomes
Artificial Intelligence · 2000–2018
A researcher in the Science corpus: 11 papers; trusts 45 researchers and is trusted by 33 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 49 citations into it; #11,604 of 35,345 by trust here, #10,798 by citations
- Optimization & Training — 31 citations into it; #1,411 of 2,601 by trust here, #1,385 by citations
- Computer Vision and Pattern Recognition — 20 citations into it
- Probabilistic & Bayesian Methods — 20 citations into it
- Ecological Modeling — 16 citations into it
- Ecology — 15 citations into it; #9,351 of 10,717 by trust here, #6,392 by citations
- Computational Theory and Mathematics — 14 citations into it; #2,497 of 12,182 by trust here, #4,850 by citations
- Nature and Landscape Conservation — 11 citations into it
Whom Carla P. Gomes trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Andreas Krause
- Geoffrey E. Hinton
- Radford M. Neal
- Michael I. Jordan
- Yoshua Bengio
- Alex Krizhevsky
- Kaiming He
- Yann LeCun
- Carlos Guestrin
- Diederik P. Kingma
Who trusts Carla P. Gomes overall
- Frank Hutter
- Jussi Rintanen
- Lars Kotthoff
- Sunny L. Jardine
- Holger H. Hoos
- Kevin Leyton-Brown
- Mustafa Misir
- Matthew J. Streeter
- Vaishak Belle
- Casey Devet
Papers from Carla P. Gomes's perspective
Ordered by how strongly the researchers Carla P. Gomes 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)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- 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
- Understanding Batch Normalization (2018) — 751 citations
- Taming the Curse of Dimensionality: Discrete Integration by Hashing and Optimization (2013) — 132 citations
- Heavy-Tailed Phenomena in Satisfiability and Constraint Satisfaction Problems (2000) — 448 citations
- Algorithm portfolios (2001) — 506 citations
- Structure and Randomness (2006) — 60 citations
- Computational Sustainability (2011) — 98 citations
- The eBird enterprise: An integrated approach to development and application of citizen science (2014) — 1,001 citations
- Designing Fast Absorbing Markov Chains (2014) — 19 citations
- Embed and Project: Discrete Sampling with Universal Hashing (2013) — 76 citations
- Solving Connected Subgraph Problems in Wildlife Conservation (2010) — 130 citations
- Backdoors to typical case complexity (2003) — 389 citations