diff --git a/.gitignore b/.gitignore
index 557b811..fa78fbc 100644
--- a/.gitignore
+++ b/.gitignore
@@ -54,6 +54,9 @@ Icon?
 ehthumbs.db
 Thumbs.db
 
+setup.cfg
+dist/
+
 # Exclude externalisation results from tikz
 tikz*.pdf
 *.md5
diff --git a/bayesnewton/models.py b/bayesnewton/models.py
index 7284089..4133057 100644
--- a/bayesnewton/models.py
+++ b/bayesnewton/models.py
@@ -58,7 +58,7 @@ def __init__(self, kernel, likelihood, X, Y):
 
 class SparseVariationalGP(VariationalInference, SparseGaussianProcess):
     """
-    Sparse variational Gaussian process (SVGP) [1], adapted to use conjugate computation VI [2]
+    Sparse variational Gaussian process (SVGP) [1, 2]
     :param kernel: a kernel object
     :param likelihood: a likelihood object
     :param X: inputs
@@ -67,8 +67,7 @@ class SparseVariationalGP(VariationalInference, SparseGaussianProcess):
     :param opt_z: boolean determining whether to optimise the inducing input locations
 
     [1] Hensman, Matthews, Ghahramani: Scalable Variational Gaussian Process Classification, AISTATS 2015
-    [2] Khan, Lin: Conugate-Computation Variational Inference - Converting Inference in Non-Conjugate Models in to
-                   Inference in Conjugate Models, AISTATS 2017
+    [2] Adam, Chang, Khan, Solin: Dual Parameterization of Sparse Variational Gaussian Processes, NeurIPS 2021
     """
     def __init__(self, kernel, likelihood, X, Y, Z, opt_z=False):
         super().__init__(kernel, likelihood, X, Y, Z, opt_z)
diff --git a/setup.py b/setup.py
index 488d453..8a7d75d 100644
--- a/setup.py
+++ b/setup.py
@@ -1,6 +1,6 @@
 from setuptools import setup, find_packages
 
-__version__ = "0.0.0"
+__version__ = "1.1"
 
 setup(
     name='bayesnewton',