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JuliaManifolds · Jul 14, 2023 · 98adc93 · 98adc93
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diff --git a/docs/src/functions/proximal_maps.md b/docs/src/functions/proximal_maps.md
@@ -29,6 +29,6 @@ Pages   = ["proximal_maps.jl"]
 # Literature
 
 ```@bibliography
-Pages = ["functions/proximal\_maps.md"]
+Pages = ["functions/proximal_maps.md"]
 Canonical=false
 ```
diff --git a/docs/src/references.bib b/docs/src/references.bib
@@ -61,6 +61,20 @@ @article{BergmannGousenbourger:2018
     NOTE         = {arXiv: [1807.10090](https://arxiv.org/abs/1807.10090)}
 }
 
+@article{BergmannHerzogSilvaLouzeiroTenbrinckVidalNunez:2021,
+    AUTHOR       = {Bergmann, Ronny and Herzog, Roland and Silva Louzeiro, Maurício and Tenbrinck, Daniel and Vidal-Núñez, José},
+    PUBLISHER    = {Springer Science and Business Media LLC},
+    YEAR         = {2021},
+    MONTH        = jan,
+    DOI          = {10.1007/s10208-020-09486-5},
+    JOURNAL      = {Foundations of Computational Mathematics},
+    NUMBER       = {6},
+    PAGES        = {1465--1504},
+    TITLE        = {Fenchel duality theory and a primal-dual algorithm on Riemannian manifolds},
+    VOLUME       = {21},
+    NOTE         = {arXiv: [1908.02022](http://arxiv.org/abs/1908.02022)}
+}
+
 @article{BergmannLausSteidlWeinmann:2014:1,
     AUTHOR       = {Bergmann, Ronny and Laus, Friederike and Steidl, Gabriele and Weinmann, Andreas},
     DOI          = {10.1137/140969993},
@@ -120,9 +134,21 @@ @techreport{deCasteljau:1963
     AUTHOR    = {de Casteljau, Paul},
     institution = {Microfiche P 4147-1, Institute National de la Propriété Industrielle, Paris.},
     TITLE     = {Courbes et surfaces à pôles},
-    YEAR      = {1959}
+    YEAR      = {1963}
+}
+
+@article{ChambollePock:2011,
+    AUTHOR       = {Chambolle, Antonin and Pock, Thomas},
+    YEAR         = {2011},
+    DOI          = {10.1007/s10851-010-0251-1},
+    JOURNAL      = {Journal of Mathematical Imaging and Vision},
+    NUMBER       = {1},
+    PAGES        = {120--145},
+    TITLE        = {A first-order primal-dual algorithm for convex problems with applications to imaging},
+    VOLUME       = {40}
 }
 
+
 @article{DuranMoelleSbertCremers:2016,
     AUTHOR   = {Duran, J. and Moeller, M. and Sbert, C. and Cremers, D.},
     TITLE    = {Collaborative Total Variation: A General Framework for Vectorial TV Models},
@@ -178,6 +204,6 @@ @article{PopielNoakes:2007
     NUMBER    = {2},
     PAGES     = {111--127},
     AUTHOR    = {Tomasz Popiel and Lyle Noakes},
-    TITLE     = {Bézier curves and ``C^2`` interpolation in Riemannian manifolds},
+    TITLE     = {Bézier curves and $C^2$ interpolation in Riemannian manifolds},
     JOURNAL   = {Journal of Approximation Theory}
 }
diff --git a/docs/src/solvers/ChambollePock.md b/docs/src/solvers/ChambollePock.md
@@ -1,6 +1,6 @@
 # [The Riemannian Chambolle-Pock Algorithm](@id ChambollePockSolver)
 
-The Riemannian Chambolle–Pock is a generalization of the Chambolle–Pock algorithm[^ChambollePock2011].
+The Riemannian Chambolle–Pock is a generalization of the Chambolle–Pock algorithm [ChambollePock:2011](@citet*).
 It is also known as primal-dual hybrid gradient (PDHG) or primal-dual proximal splitting (PDPS) algorithm.
 
 In order to minimize over $p∈\mathcal M§ the cost function consisting of
@@ -17,7 +17,7 @@ such that $Λ(\mathcal C) \subset \mathcal D$.
 
 The algorithm is available in four variants: exact versus linearized (see `variant`)
 as well as with primal versus dual relaxation (see `relax`). For more details, see
-[^BergmannHerzogSilvaLouzeiroTenbrinckVidalNunez2020].
+[BergmannHerzogSilvaLouzeiroTenbrinckVidalNunez:2021](@citet*).
 In the following we note the case of the exact, primal relaxed Riemannian Chambolle–Pock algorithm.
 
 Given base points $m∈\mathcal C$, $n=Λ(m)∈\mathcal D$,
@@ -107,8 +107,9 @@ RecordPrimalIterate
 Manopt.update_prox_parameters!
 ```
 
-[^ChambollePock2011]:
-    > A. Chambolle, T. Pock:
-    > _A first-order primal-dual algorithm for convex problems with applications to imaging_,
-    > Journal of Mathematical Imaging and Vision 40(1), 120–145, 2011.
-    > doi: [10.1007/s10851-010-0251-1](https://dx.doi.org/10.1007/s10851-010-0251-1)
+## Literature
+
+```@bibliography
+Pages = ["solvers/ChambollePock.md"]
+Canonical=false
+```
diff --git a/src/solvers/ChambollePock.jl b/src/solvers/ChambollePock.jl
@@ -195,7 +195,7 @@ allocating functions `(Manifolds, parameters) -> result`  or as mutating functio
 By default, this performs the exact Riemannian Chambolle Pock algorithm, see the optional parameter
 `DΛ` for their linearized variant.
 
-For more details on the algorithm, see[^BergmannHerzogSilvaLouzeiroTenbrinckVidalNunez2020].
+For more details on the algorithm, see [Bergmann et al., Found. Comput. Math., 2021](@cite BergmannHerzogSilvaLouzeiroTenbrinckVidalNunez:2021).
 
 # Optional Parameters
 
@@ -220,14 +220,7 @@ For more details on the algorithm, see[^BergmannHerzogSilvaLouzeiroTenbrinckVida
 
 # Output
 
-the obtained (approximate) minimizer ``p^*``, see [`get_solver_return`](@ref) for details
-
-[^BergmannHerzogSilvaLouzeiroTenbrinckVidalNunez2020]:
-    > R. Bergmann, R. Herzog, M. Silva Louzeiro, D. Tenbrinck, J. Vidal-Núñez:
-    > _Fenchel Duality Theory and a Primal-Dual Algorithm on Riemannian Manifolds_,
-    > Foundations of Computational Mathematics, 2021.
-    > doi: [10.1007/s10208-020-09486-5](http://dx.doi.org/10.1007/s10208-020-09486-5)
-    > arXiv: [1908.02022](http://arxiv.org/abs/1908.02022)
+the obtained (approximate) minimizer ``p^*``, see [`get_solver_return`](@ref) for details.
 """
 function ChambollePock(
     M::AbstractManifold,