Parallel Poster Sessions
Workshop: XXAI: Extending Explainable AI Beyond Deep Models and Classifiers

Poster Session 2

Wojciech Samek


Zoom Room 1

  • Bhatt et al. "Machine Learning Explainability for External Stakeholders"
  • Karimi et al. "Algorithmic recourse under imperfect causal knowledge: a probabilistic approach"
  • Wang et al. "Towards Probabilistic Sufficient Explanations"

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Zoom Room 2

  • Agarwal et al. "Neural Additive Models: Interpretable Machine Learning with Neural Nets"
  • Alaniz et al. "Learning Decision Trees Recurrently through Communication"
  • Anders et al. "XAI for Analyzing and Unlearning Spurious Correlations in ImageNet"

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Zoom Room 3

  • Dasgupta et al. "Explainable k-Means Clustering: Theory and Practice"
  • Dhurandhar et al. "Leveraging Simple Model Predictions for Enhancing its Performance"
  • Brophy and Lowd: "TREX: Tree-Ensemble Representer-Point Explanations"

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Zoom Room 4

  • Lin et al. "Contrastive Explanations for Reinforcement Learning via Embedded Self Predictions"
  • Yau et al. "What Did You Think Would Happen? Explaining Agent Behaviour through Intended Outcomes"
  • Danesh et al. "Understanding Finite-State Representations of Recurrent Policy Networks"

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Zoom Room 5

  • Quint et al. "Contrastive Attribution with Feature Visualization"
  • Zhao "Fast Real-time Counterfactual Explanations"
  • Chrysos et al. "Unsupervised Controllable Generation with Self-Training"

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