V. Boehm

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom V. Boehm trusts overall

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

  1. W. James Murdoch

Papers from V. Boehm's perspective

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

  1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  2. Axiomatic Attribution for Deep Networks
  3. Latent Dirichlet Allocation
  4. Association for Computational Linguistics " Why Should I Trust You? " Explaining the Predictions of Any Classifier
  5. On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation
  6. Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization
  7. A Unified Approach to Interpreting Model Predictions
  8. Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs
  9. Towards better understanding of gradient-based attribution methods for Deep Neural Networks
  10. Not Just a Black Box: Learning Important Features Through Propagating Activation Differences

Their papers