Raquel Rodríguez-Pérez
Computational Theory and Mathematics · 2020
A researcher in the Science corpus: 2 papers; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computational Theory and Mathematics — 24 citations into it
- Molecular Biology — 16 citations into it
- Artificial Intelligence — 15 citations into it
- Materials Chemistry — 10 citations into it
- Statistics and Probability — 8 citations into it
- Computer Vision and Pattern Recognition — 5 citations into it
- Safety, Robustness & Interpretability — 5 citations into it
Whom Raquel Rodríguez-Pérez trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Lloyd S. Shapley
- Scott M. Lundberg
- Bradley Efron
- Martin J. Osborne
- Trevor J. Hastie
- Jerome H. Friedman
- Andrea Saltelli
- Radford M. Neal
- Su-In Lee
- Ariel Rubinstein
Who trusts Raquel Rodríguez-Pérez overall
Papers from Raquel Rodríguez-Pérez's perspective
Ordered by how strongly the researchers Raquel Rodríguez-Pérez trusts endorse each paper. Same corpus, a different order for every researcher.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Scikit-learn: Machine Learning in Python
- ImageNet Large Scale Visual Recognition Challenge
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- Pattern Recognition and Machine Learning
- TensorFlow: A system for large-scale machine learning
- A Value for n-person Games
Their papers
- Interpretation of machine learning models using shapley values: application to compound potency and multi-target activity predictions (2020) — 617 citations
- Interpretation of Compound Activity Predictions from Complex Machine Learning Models Using Local Approximations and Shapley Values. (2020) — 428 citations