diff --git a/Dockerfile b/Dockerfile
index 3e29f88..b517fe3 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -42,7 +42,7 @@ RUN make dist
 FROM cebra-base
 
 # install the cebra wheel
-ENV WHEEL=cebra-0.3.1-py2.py3-none-any.whl
+ENV WHEEL=cebra-0.4.0-py2.py3-none-any.whl
 WORKDIR /build
 COPY --from=wheel /build/dist/${WHEEL} .
 RUN pip install --no-cache-dir ${WHEEL}'[dev,integrations,datasets]'
diff --git a/Makefile b/Makefile
index 16abfb9..9f94561 100644
--- a/Makefile
+++ b/Makefile
@@ -1,4 +1,4 @@
-CEBRA_VERSION := 0.3.1
+CEBRA_VERSION := 0.4.0
 
 dist:
 	python3 -m pip install virtualenv
diff --git a/PKGBUILD b/PKGBUILD
index e4edb49..07fa3a1 100644
--- a/PKGBUILD
+++ b/PKGBUILD
@@ -1,7 +1,7 @@
 # Maintainer: Steffen Schneider <stes@hey.com>
 pkgname=python-cebra
 _pkgname=cebra
-pkgver=0.3.1
+pkgver=0.4.0
 pkgrel=1
 pkgdesc="Consistent Embeddings of high-dimensional Recordings using Auxiliary variables"
 url="https://cebra.ai"
diff --git a/cebra/__init__.py b/cebra/__init__.py
index ff9bc33..fd4cf58 100644
--- a/cebra/__init__.py
+++ b/cebra/__init__.py
@@ -66,7 +66,7 @@
 
 import cebra.integrations.sklearn as sklearn
 
-__version__ = "0.3.1"
+__version__ = "0.4.0"
 __all__ = ["CEBRA"]
 __allow_lazy_imports = False
 __lazy_imports = {}
diff --git a/reinstall.sh b/reinstall.sh
index 9eb6d8c..778f98e 100755
--- a/reinstall.sh
+++ b/reinstall.sh
@@ -15,7 +15,7 @@ pip uninstall -y cebra
 # Get version info after uninstalling --- this will automatically get the
 # most recent version based on the source code in the current directory.
 # $(tools/get_cebra_version.sh)
-VERSION=0.3.1
+VERSION=0.4.0
 echo "Upgrading to CEBRA v${VERSION}"
 
 # Upgrade the build system (PEP517/518 compatible)
diff --git a/tests/test_criterions.py b/tests/test_criterions.py
index 24c4775..9d176be 100644
--- a/tests/test_criterions.py
+++ b/tests/test_criterions.py
@@ -259,10 +259,10 @@ def _reference_infonce(pos_dist, neg_dist):
 
 
 def test_similiarities():
-
-    ref = torch.randn(10, 3)
-    pos = torch.randn(10, 3)
-    neg = torch.randn(12, 3)
+    rng = torch.Generator().manual_seed(42)
+    ref = torch.randn(10, 3, generator = rng)
+    pos = torch.randn(10, 3, generator = rng)
+    neg = torch.randn(12, 3, generator = rng)
 
     pos_dist, neg_dist = _reference_dot_similarity(ref, pos, neg)
     pos_dist_2, neg_dist_2 = cebra_criterions.dot_similarity(ref, pos, neg)