Update README.md

README.md

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 # Complex contagions can outperform simple contagions for network reconstruction with dense networks or saturated dynamics
 
-This repository accompanies the preprint "Complex contagions can outperform simple contagions for network reconstruction with dense networks or saturated dynamics" by Nicholas Landry, Will Thompson, Laurent Hébert-Dufresne, and Jean-Gabriel Young.
+This repository accompanies the preprint ["Complex contagions can outperform simple contagions for network reconstruction with dense networks or saturated dynamics"](https://arxiv.org/abs/2405.00129) by Nicholas Landry, Will Thompson, Laurent Hébert-Dufresne, and Jean-Gabriel Young.
 
 ### The structure of this repository is as follows:
 * The `Data` folder contains all of the data corresponding to the figures in the manuscript.
@@ -34,4 +34,4 @@ This repository accompanies the preprint "Complex contagions can outperform simp
 * `collect_zkc_infer_vs_tmax.py` and `collect_zkc_frac_vs_beta` collect this data and measure the performance of the reconstructions for Figs. 1(c) and 1(d) respectively.
 
 ### Notebooks
-* `run_dynamical_inference.ipynb` runs a single inference for a single network and time series.
+* `run_dynamical_inference.ipynb` runs a single inference for a single network and time series.