Felipe Oviedo

Artificial Intelligence · with Buonassisi · 2018–2021

A researcher in the Science corpus: 2 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 14 citations into it
• Safety, Robustness & Interpretability — 6 citations into it

Whom Felipe Oviedo trusts overall

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

1. Bradley C. Boehmke
2. Brandon M. Greenwell
3. Bolei Zhou
4. Mélanie Frappier
5. Simon J. L. Billinge

Papers from Felipe Oviedo's perspective

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

1. Deep Learning
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Gradient-based learning applied to document recognition
5. I and J
6. Long Short-Term Memory
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Going deeper with convolutions
9. Learning Multiple Layers of Features from Tiny Images
10. Learning Deep Features for Discriminative Localization

Their papers

• Interpretable and Explainable Machine Learning for Materials Science and Chemistry (2021) — 311 citations
• Fast and interpretable classification of small X-ray diffraction datasets using data augmentation and deep neural networks (2018) — 301 citations