Usue Mori

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Usue Mori trusts overall

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

  1. Eamonn J. Keogh
  2. Alexey Tsymbal
  3. Lexiang Ye
  4. David J. Hill
  5. Oded Z. Maimon
  6. Mayu Sakurada

Papers from Usue Mori's perspective

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

  1. HOT SAX: efficiently finding the most unusual time series subsequence (Industrial Conference on Data Mining)
  2. Finding surprising patterns in a time series database in linear time and space (Knowledge Discovery and Data Mining)
  3. Unsupervised real-time anomaly detection for streaming data (Neurocomputing)
  4. Generic and Scalable Framework for Automated Time-series Anomaly Detection (Knowledge Discovery and Data Mining)
  5. Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding (Knowledge Discovery and Data Mining)
  6. Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network (Knowledge Discovery and Data Mining)
  7. Time series shapelets: a new primitive for data mining (Knowledge Discovery and Data Mining)
  8. Anomaly Detection Using Autoencoders with Nonlinear Dimensionality Reduction
  9. Anomaly detection in streaming environmental sensor data: A data-driven modeling approach (Environmental Modelling & Software)
  10. White Rose Consortium ePrints Repository

Their papers