diff --git a/causy/causal_discovery/constraint/independence_tests/common.py b/causy/causal_discovery/constraint/independence_tests/common.py
index fe4d4b7..55101ee 100644
--- a/causy/causal_discovery/constraint/independence_tests/common.py
+++ b/causy/causal_discovery/constraint/independence_tests/common.py
@@ -170,9 +170,17 @@ def process(
 
         if not set(nodes[2:]).issubset(set([on for on in list(other_neighbours)])):
             return
-        inverse_cov_matrix = torch.inverse(
-            torch.cov(torch.stack([graph.nodes[node].values for node in nodes]))
+        cov_matrix = torch.cov(
+            torch.stack([graph.nodes[node].values for node in nodes])
         )
+        # check if the covariance matrix is ill-conditioned
+        if torch.det(cov_matrix) == 0:
+            logger.warning(
+                "The covariance matrix is ill-conditioned. The precision matrix is not reliable."
+            )
+            return
+
+        inverse_cov_matrix = torch.inverse(cov_matrix)
 
         n = inverse_cov_matrix.size(0)
         diagonal = torch.diag(inverse_cov_matrix)
@@ -186,15 +194,22 @@ def process(
         sample_size = len(graph.nodes[nodes[0]].values)
         nb_of_control_vars = len(nodes) - 2
 
-        t, critical_t = get_t_and_critical_t(
-            sample_size,
-            nb_of_control_vars,
-            (
-                (-1 * precision_matrix[0][1])
-                / torch.sqrt(precision_matrix[0][0] * precision_matrix[1][1])
-            ).item(),
-            self.threshold,
-        )
+        # prevent math domain error
+        try:
+            t, critical_t = get_t_and_critical_t(
+                sample_size,
+                nb_of_control_vars,
+                (
+                    (-1 * precision_matrix[0][1])
+                    / torch.sqrt(precision_matrix[0][0] * precision_matrix[1][1])
+                ).item(),
+                self.threshold,
+            )
+        except ValueError:
+            logger.warning(
+                "Math domain error. The covariance matrix is ill-conditioned. The precision matrix is not reliable."
+            )
+            return
 
         if abs(t) < critical_t:
             logger.debug(
diff --git a/poetry.lock b/poetry.lock
index e076156..ad70f3f 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -135,63 +135,83 @@ files = [
 
 [[package]]
 name = "coverage"
-version = "7.5.4"
+version = "7.6.1"
 description = "Code coverage measurement for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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 socks = ["socksio (==1.*)"]
 trio = ["trio (>=0.22.0,<0.26.0)"]
 
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 [[package]]
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 version = "24.1"
@@ -1032,13 +854,13 @@ files = [
 
 [[package]]
 name = "pdoc"
-version = "14.5.1"
+version = "14.6.0"
 description = "API Documentation for Python Projects"
 optional = false
 python-versions = ">=3.8"
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 [package.dependencies]
@@ -1067,13 +889,13 @@ type = ["mypy (>=1.8)"]
 
 [[package]]
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+version = "3.8.0"
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 python-versions = ">=3.9"
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@@ -1111,7 +933,10 @@ files = [
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-typing-extensions = {version = ">=4.6.1", markers = "python_version < \"3.13\""}
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+    {version = ">=4.6.1", markers = "python_version < \"3.13\""},
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 [package.extras]
 email = ["email-validator (>=2.0.0)"]
@@ -1254,108 +1079,81 @@ windows-terminal = ["colorama (>=0.4.6)"]
 
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-[package.extras]
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-
 [[package]]
 name = "pyyaml"
 version = "6.0.1"
@@ -1653,71 +1451,60 @@ full = ["httpx (>=0.22.0)", "itsdangerous", "jinja2", "python-multipart (>=0.0.7
 
 [[package]]
 name = "sympy"
-version = "1.12.1"
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 [package.dependencies]
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 fsspec = "*"
 jinja2 = "*"
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 networkx = "*"
 nvidia-cublas-cu12 = {version = "12.1.3.1", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
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 nvidia-cuda-nvrtc-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cuda-runtime-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cudnn-cu12 = {version = "8.9.2.26", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cudnn-cu12 = {version = "9.1.0.70", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cufft-cu12 = {version = "11.0.2.54", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
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 nvidia-cusolver-cu12 = {version = "11.4.5.107", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
@@ -1725,26 +1512,30 @@ nvidia-cusparse-cu12 = {version = "12.1.0.106", markers = "platform_system == \"
 nvidia-nccl-cu12 = {version = "2.20.5", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-nvtx-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 sympy = "*"
-triton = {version = "2.3.1", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.12\""}
+triton = {version = "3.0.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.13\""}
 typing-extensions = ">=4.8.0"
 
 [package.extras]
 opt-einsum = ["opt-einsum (>=3.3)"]
-optree = ["optree (>=0.9.1)"]
+optree = ["optree (>=0.11.0)"]
 
 [[package]]
 name = "triton"
-version = "2.3.1"
+version = "3.0.0"
 description = "A language and compiler for custom Deep Learning operations"
 optional = false
 python-versions = "*"
 files = [
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 [package.dependencies]
@@ -1752,8 +1543,8 @@ filelock = "*"
 
 [package.extras]
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+tutorials = ["matplotlib", "pandas", "tabulate"]
 
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-
 [[package]]
 name = "zipp"
 version = "3.19.2"
@@ -2155,5 +1640,5 @@ test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools",
 
 [metadata]
 lock-version = "2.0"
-python-versions = ">=3.11,<3.13"
-content-hash = "d8f1be7c29f9842b9a8b39373e943ae344402d98f0693122f2c82ede4c62ef33"
+python-versions = "^3.11"
+content-hash = "d5df0d88a9d6d01be4bf54f96f1f0399e639f6c1fa5d5607d6ae7cb5c8b6ec20"
diff --git a/pyproject.toml b/pyproject.toml
index 31e1cb7..f896bcb 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -8,12 +8,12 @@ license = "MIT"
 include = ["pyproject.toml", "README.md", "LICENSE", "causy", "causy/static/*", "causy/static/assets/*"]
 
 [tool.poetry.dependencies]
-python = ">=3.11,<3.13"
+python = "^3.11"
 scipy = "^1.14"
 typer = {extras = ["all"], version = "^0.12.3"}
-torch = "^2.3.1"
-fastapi = "^0.111.0"
-uvicorn = "^0.30.1"
+torch = "^2.4"
+fastapi = "^0.112.0"
+uvicorn = "^0.30.5"
 srsly = "^2.4.8"
 pydantic-yaml = "^1.2.1"
 click = "^8.1.7"