T. S. Filho
Artificial Intelligence · 2017–2019
A researcher in the Science corpus: 4 papers; trusts 25 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 22 citations into it; #19,817 of 35,345 by trust here, #25,040 by citations
- Evaluation & Benchmarks — 11 citations into it; #2,219 of 3,147 by trust here, #3,134 by citations
- Computer Vision and Pattern Recognition — 5 citations into it
- Probabilistic & Bayesian Methods — 5 citations into it
Whom T. S. Filho trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Jaka Demsar
- Bianca Zadrozny
- Trevor J. Hastie
- Alex Smola
- Charles Peter Elkan
- Mark A. Hall
- Alexandru Niculescu-Mizil
- Peter L. Bartlett
- Bernhard Schölkopf
- Fabian Pedregosa
Who trusts T. S. Filho overall
- Eyke Hüllermeier
- Ananya Kumar
- Meelis Kull
- Kyle Cranmer
- Willem Waegeman
- Jessa Bekker
- Jonathan Wenger
- Rogelio Andrade Mancisidor
- Fabian Küppers
- Gia-Lac Tran
Papers from T. S. Filho's perspective
Ordered by how strongly the researchers T. S. Filho trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration (2019) — 547 citations
- Beyond sigmoids: How to obtain well-calibrated probabilities from binary classifiers with beta calibration (2017) — 128 citations
- Beta calibration: a well-founded and easily implemented improvement on logistic calibration for binary classifiers (2017) — 295 citations
- Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS 2017) (2017) — 6 citations