Ralf Wieland

Artificial Intelligence · 2008–2021

A researcher in the Science corpus: 3 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Ralf Wieland trusts overall

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

  1. Xia Li
  2. Tianqi Chen
  3. Jesse Davis
  4. Elizabeth A. Freeman
  5. Yingzhi Lin
  6. Xun Liang
  7. Carlos Guestrin
  8. Anthony Gar-On Yeh
  9. Mark H. Goadrich
  10. Fabian Pedregosa

Papers from Ralf Wieland's perspective

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

  1. Neural-network-based cellular automata for simulating multiple land use changes using GIS (International Journal of Geographical Information Science)
  2. XGBoost: A Scalable Tree Boosting System
  3. Scikit-learn: Machine Learning in Python
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. A Unified Approach to Interpreting Model Predictions
  6. The relationship between Precision-Recall and ROC curves
  7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  8. Delineating multi-scenario urban growth boundaries with a CA-based FLUS model and morphological method (Landscape and Urban Planning)
  9. ImageNet classification with deep convolutional neural networks
  10. Gradient-based learning applied to document recognition

Their papers