Merge pull request #78 from JuliaTrustworthyAI/76-revise-extended-abs…

…tract

76 revise extended abstract

paper/paper.aux

@@ -16,6 +16,10 @@
 \citation{goodfellow2014explaining}
 \citation{wilson2020case}
 \citation{wilson2020case}
+\citation{daxberger2021laplace}
+\citation{ish-horowicz2019interpreting}
+\citation{schut2021generating}
+\citation{altmeyer2023faithful}
 \citation{blundell2015weight}
 \citation{gal2016dropout}
 \citation{lakshminarayanan2016simple}
@@ -24,6 +28,7 @@
 \citation{martens2015optimizing}
 \citation{lawrence2001variational}
 \citation{immer2020improving}
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 \citation{daxberger2021laplace}
 \citation{immer2020improving}
 \citation{daxberger2021laplace}
@@ -39,8 +44,6 @@
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 \citation{martens2020optimizing}
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-\bibcite{lakshminarayanan2016simple}{7}
-\bibcite{lawrence2001variational}{8}
-\bibcite{martens2015optimizing}{9}
-\bibcite{martens2020optimizing}{10}
-\bibcite{wilson2020case}{11}
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+\bibcite{altmeyer2023faithful}{1}
+\bibcite{antoran2023samplingbased}{2}
+\bibcite{blundell2015weight}{3}
+\bibcite{daxberger2021laplace}{4}
+\bibcite{gal2016dropout}{5}
+\bibcite{goodfellow2014explaining}{6}
+\bibcite{immer2020improving}{7}
+\bibcite{ish-horowicz2019interpreting}{8}
+\bibcite{lakshminarayanan2016simple}{9}
+\bibcite{lawrence2001variational}{10}
+\bibcite{martens2015optimizing}{11}
+\bibcite{martens2020optimizing}{12}
+\bibcite{schut2021generating}{13}
+\bibcite{wilson2020case}{14}
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paper/paper.bbl

@@ -1,5 +1,10 @@
 \begin{thebibliography}{10}
 
+\bibitem{altmeyer2023faithful}
+Patrick Altmeyer, Mojtaba Farmanbar, Arie van Deursen, and Cynthia C.~S. Liem.
+Faithful model explanations through energy-constrained conformal counterfactuals, 2023.
+2312.10648.
+
 \bibitem{antoran2023samplingbased}
 Javier Antorán, Shreyas Padhy, Riccardo Barbano, Eric Nalisnick, David Janz, and José~Miguel Hernández-Lobato.
 Sampling-based inference for large linear models, with application to linearised laplace, 2023.
@@ -30,6 +35,11 @@ Alexander Immer, Maciej Korzepa, and Matthias Bauer.
 Improving predictions of bayesian neural networks via local linearization.
 arxiv:\href{http://arxiv.org/abs/2008.08400}{2008.08400}.
 
+\bibitem{ish-horowicz2019interpreting}
+Jonathan Ish-Horowicz, Dana Udwin, Seth Flaxman, Sarah Filippi, and Lorin Crawford.
+Interpreting deep neural networks through variable importance.
+arxiv:\href{http://arxiv.org/abs/1901.09839}{1901.09839}.
+
 \bibitem{lakshminarayanan2016simple}
 Balaji Lakshminarayanan, Alexander Pritzel, and Charles Blundell.
 Simple and scalable predictive uncertainty estimation using deep ensembles.
@@ -49,6 +59,11 @@ James Martens and Roger Grosse.
 Optimizing neural networks with kronecker-factored approximate curvature, 2020.
 1503.05671.
 
+\bibitem{schut2021generating}
+Lisa Schut, Oscar Key, Rory Mc~Grath, Luca Costabello, Bogdan Sacaleanu, Yarin Gal, et~al.
+Generating {{Interpretable Counterfactual Explanations By Implicit Minimisation}} of {{Epistemic}} and {{Aleatoric Uncertainties}}.
+In {\em International {{Conference}} on {{Artificial Intelligence}} and {{Statistics}}}, pages 1756--1764. {PMLR}.
+
 \bibitem{wilson2020case}
 Andrew~Gordon Wilson.
 The case for {{Bayesian}} deep learning.

paper/paper.blg

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