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interpretability

Palavras-chave relacioandas:


  • concept vectors
  • Deep convolutional neural network
  • Deep Learning
  • EEG
  • explainability
  • explainable AI (XAI)
  • explainable artificial intelligence
  • Histopathology
  • machine learning
  • Multi-Agent Systems
  • selective attention
  • understandability
  • wrong labels
  • XAI
  • XMAS

Publicações para palavra-chave interpretability
2021
Mara Graziani, Iam Palatnik de Sousa, Marley M Vellasco BR, Eduardo Costa da Silva, Henning Müller and Vincent Andrearczyk, Sharpening Local Interpretable Model-agnostic Explanations for Histopathology: Improved Understandability and Reliability, in: MICCAI 2021, Springer, 2021
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Lora Fanda, Yashin Dicente Cid, Paweł J Matusz and Davide Calvaresi, To Pay or Not to Pay Attention: Classifying and Interpreting Visual Selective Attention Frequency Features, 2021
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2020
giovanni ciatto, Andrea Omicini, Michael Schumacher and Davide Calvaresi, Agent-Based Explanations in AI: Towards an Abstract Framework, in: Post-Proceedings o EXTRAAMAS 2020, Springer, 2020
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2019
Mara Graziani, Henning Müller and Vincent Andrearczyk, Interpreting intentionally flawed models with linear probes, in: ICCV workshop on statistical deep learning in computer vision, Seoul, Korea, 2019
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2018
Mara Graziani, Vincent Andrearczyk and Henning Müller, Regression Concept Vectors for Bidirectional Explanations in Histopathology (2018), in: Lecture Notes in Computer Science, Workshop on Interpretability of Machine Intelligence in Medical Image Computing at MICCAI 2018(8)
  • []: Best paper award

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