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Added references and links to pdfs

README.md

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 > Open-source, implicit 3D structural geological modeling in Python.
 
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@@ -52,12 +51,15 @@ If you find a bug or have a feature request, create an [issue](https://github.co
 <a name="ref"></a>
 ## References 
 
-* de la Varga, M., Schaaf, A., and Wellmann, F.: GemPy 1.0: open-source stochastic geological modeling and inversion, Geosci. Model Dev., 12, 1-32, https://doi.org/10.5194/gmd-12-1-2019, 2019
+* de la Varga, M., Schaaf, A., and Wellmann, F. (2019). [GemPy 1.0: open-source stochastic geological modeling and inversion](https://gmd.copernicus.org/articles/12/1/2019/gmd-12-1-2019.pdf), Geosci. Model Dev., 12, 1-32, https://doi.org/10.5194/gmd-12-1-2019.
+* Wellmann, F., & Caumon, G. (2018). [3-D Structural geological models: Concepts, methods, and uncertainties.](https://hal.univ-lorraine.fr/hal-01921494/file/structural_models_for_geophysicsHAL.pdf) In Advances in Geophysics (Vol. 59, pp. 1-121). Elsevier.
 * Calcagno, P., Chilès, J. P., Courrioux, G., & Guillen, A. (2008). Geological modelling from field data and geological knowledge: Part I. Modelling method coupling 3D potential-field interpolation and geological rules. Physics of the Earth and Planetary Interiors, 171(1-4), 147-157.
 * Lajaunie, C., Courrioux, G., & Manuel, L. (1997). Foliation fields and 3D cartography in geology: principles of a method based on potential interpolation. Mathematical Geology, 29(4), 571-584.
 
 ## Publications using GemPy
 
+* Güdük, N., de la Varga, M. Kaukolinna, J. and Wellmann, F. (in review). Model-Based Probabilistic Inversion Using Magnetic Data: A Case Study on the Kevitsa Deposit.
+* Schaaf, A., de la Varga, M., Wellmann, F., & Bond, C. E. (2020). [Constraining stochastic 3-D structural geological models with topology information using Approximate Bayesian Computation using GemPy 2.1](https://gmd.copernicus.org/preprints/gmd-2020-136/gmd-2020-136.pdf). Geoscientific Model Development Discussions, 1-24.
 * Stamm, F. A., de la Varga, M., and Wellmann, F.: [Actors, actions, and uncertainties: optimizing decision-making based on 3-D structural geological models](https://se.copernicus.org/articles/10/2015/2019/se-10-2015-2019.html), Solid Earth, 10, 2015–2043, https://doi.org/10.5194/se-10-2015-2019, 2019.
 * Wellmann, F., Schaaf, A., de la Varga, M., & von Hagke, C. (2019). [From Google Earth to 3D Geology Problem 2: Seeing Below the Surface of the Digital Earth](
 https://www.sciencedirect.com/science/article/pii/B9780128140482000156).