Sebastian Schmidl

Artificial Intelligence · 2022

A researcher in the Science corpus: 1 paper; trusts 16 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Sebastian Schmidl trusts overall

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

  1. Rfdo 2XWOLHUV
  2. Eamonn J. Keogh
  3. Lovekesh Vig
  4. Peter J. Rousseeuw
  5. Mayu Sakurada
  6. Markus Goldstein
  7. Junshui Ma
  8. Michael Hahsler
  9. Dragoljub Pokrajac
  10. Sahand Hariri

Papers from Sebastian Schmidl's perspective

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

  1. Anomaly detection: A survey
  2. LOF: identifying density-based local outliers
  3. Long Short-Term Memory
  4. HOT SAX: efficiently finding the most unusual time series subsequence (Industrial Conference on Data Mining)
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Long Short Term Memory Networks for Anomaly Detection in Time Series (The European Symposium on Artificial Neural Networks)
  7. ImageNet classification with deep convolutional neural networks
  8. Efficient algorithms for mining outliers from large data sets (ACM SIGMOD Conference)
  9. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  10. Auto-Encoding Variational Bayes (International Conference on Learning Representations)

Their papers