Patrick Schratz
Statistics and Probability · 2018–2019
A researcher in the Science corpus: 2 papers; trusts 5 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Statistics and Probability — 11 citations into it
- Environmental Engineering — 10 citations into it; #5,375 of 5,479 by trust here, #4,694 by citations
- Global and Planetary Change — 8 citations into it
- Statistical Learning Theory — 7 citations into it
- Evaluation & Benchmarks — 6 citations into it
- Management, Monitoring, Policy and Law — 5 citations into it
- Management Science and Operations Research — 5 citations into it
Whom Patrick Schratz trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alexander Brenning
- Biswajeet Pradhan
- Ron Kohavi
- Alan Y. Chiang
- Trevor J. Hastie
- Max Kuhn
- Hamid Reza Pourghasemi
- Gérard Biau
- S. Wenger
- Ramón Díaz-Uriarte
Who trusts Patrick Schratz overall
Papers from Patrick Schratz's perspective
Ordered by how strongly the researchers Patrick Schratz trusts endorse each paper. Same corpus, a different order for every researcher.
- Random Forests
- The Elements of Statistical Learning: Data Mining, Inference, and Prediction
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Scikit-learn: Machine Learning in Python
- A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection
- Regression Shrinkage and Selection via the Lasso
- Random Search for Hyper-Parameter Optimization
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
Their papers
- Performance evaluation and hyperparameter tuning of statistical and machine-learning models using spatial data (2018) — 439 citations
- mlr3: A modern object-oriented machine learning framework in R (2019) — 406 citations