Update app.py

app.py

@@ -104,7 +104,7 @@ iface = gr.Interface(fn=infer,
 Lines represent means and shaded areas are the confidence interval (68.2% quantile). In green, we have the ground truth GP posterior and in blue we have our approximation.
 We provide three models that are architecturally the same, but with different training budgets.
                      ''',
-                     article="<p style='text-align: center'><a href='https://openreview.net/forum?id=KSugKcbNf9'>Paper: Transformers Can Do Bayesian Inference</a></p>",
+                     article="<p style='text-align: center'><a href='https://arxiv.org/abs/2112.10510'>Paper: Transformers Can Do Bayesian Inference</a></p>",
                      inputs=[
                          gr.inputs.Dataframe(headers=["x", "y"], datatype=["number", "number"], row_count=2, type='numpy', default=[['.25','.1'],['.75','.4']], label='The data: you can change this and increase the number of data points using the `enter` key.'),
                          gr.inputs.Radio(['160K','800K','4M'], type="value", default='160K', label='Number of Sampled Datasets in Training (Training Costs), higher values yield better results')