docs: add ref for active learning

docs/source/refs.bib

@@ -62,6 +62,16 @@
   author = "Jon Herman and Will Usher"
 }
 
+@article{Kandasamy2017,
+  title = "Query efficient posterior estimation in scientific experiments via {Bayesian} active learning",
+  journal = "Artificial Intelligence",
+  volume = "243",
+  pages = "45--56",
+  year = "2017",
+  doi = "https://doi.org/10.1016/j.artint.2016.11.002",
+  author = "Kirthevasan Kandasamy and Jeff Schneider and Barnab{\'a}s P{\'o}czos",
+}
+
 @article{LeGratiet2014,
   title = "A {Bayesian} approach for global sensitivity analysis of (multifidelity) computer codes",
   journal = "SIAM/ASA Journal on Uncertainty Quantification",
@@ -106,6 +116,17 @@
   author = "Andrea Saltelli and Paola Annoni and Ivano Azzini and Francesca Campolongo and Marco Ratto and Stefano Tarantola"
 }
 
+@article{Wang2018,
+  title   = "Adaptive {Gaussian} process approximation for {Bayesian} inference with expensive likelihood functions",
+  journal = "Neural Computation",
+  volume  = "30",
+  number  = "11",
+  pages   = "3072--3094",
+  year    = "2018",
+  doi     = "10.1162/neco_a_01127",
+  author  = "Hong Qiao Wang and Jing Lai Li"
+}
+
 @article{Zhao2021a,
   title   = "Emulator-based global sensitivity analysis for flow-like landslide run-out models",
   journal = "Landslides",
@@ -124,3 +145,15 @@
   year         = {2021},
   doi          = {10.18154/RWTH-2021-11693}
 }
+
+@article{Zhao2022,
+  title = {Bayesian active learning for parameter calibration of landslide run-out models},
+  journal = {Landslides},
+  volume = {19},
+  number = {},
+  pages = {2033--2045},
+  year = {2022},
+  doi = {https://doi.org/10.1007/s10346-022-01857-z},
+  author = {Zhao, Hu and Kowalski, Julia}
+}
+