Asymmetric shapley values: incorporating causal knowledge into model-agnostic explainability

C Frye, C Rowat, I Feige - Advances in neural information …, 2020 - proceedings.neurips.cc
Explaining AI systems is fundamental both to the development of high performing models
and to the trust placed in them by their users. The Shapley framework for explainability has …
被引用次数：237 相关文章
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[PDF][PDF] Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability

C Frye, C Rowat, I Feige - proceedings.nips.cc
Explaining AI systems is fundamental both to the development of high performing models
and to the trust placed in them by their users. The Shapley framework for explainability has …

Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability

C Frye, C Rowat, I Feige - socscistaff.bham.ac.uk
Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability
Page 1 Asymmetric Shapley values: incorporating causal knowledge into model-agnostic …

Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability

C Frye, C Rowat, I Feige - arXiv e-prints, 2019 - ui.adsabs.harvard.edu
Explaining AI systems is fundamental both to the development of high performing models
and to the trust placed in them by their users. The Shapley framework for explainability has …

Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability

C Frye, C Rowat, I Feige - … of the 34th International Conference on …, 2020 - dl.acm.org
Explaining AI systems is fundamental both to the development of high performing models
and to the trust placed in them by their users. The Shapley framework for explainability has …

Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability

C Frye, C Rowat, I Feige - Advances in Neural Information …, 2020 - proceedings.neurips.cc
Explaining AI systems is fundamental both to the development of high performing models
and to the trust placed in them by their users. The Shapley framework for explainability has …

Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability

I Feige, C Rowat, C Frye - 2020 - research.birmingham.ac.uk
Explaining AI systems is fundamental both to the development of high performing models
and to the trust placed in them by their users. A general framework for explaining any AI …

Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability

C Frye, C Rowat, I Feige - arXiv preprint arXiv:1910.06358, 2019 - arxiv.org
Explaining AI systems is fundamental both to the development of high performing models
and to the trust placed in them by their users. The Shapley framework for explainability has …