Use Cauchy distribution for BNN biases

gpax/models/bnn.py

@@ -47,7 +47,7 @@ def sample_weights(name: str, in_channels: int, out_channels: int) -> jnp.ndarra
 
 def sample_biases(name: str, channels: int) -> jnp.ndarray:
     """Sampling bias vector"""
-    b = numpyro.sample(name=name, fn=dist.Normal(
+    b = numpyro.sample(name=name, fn=dist.Cauchy(
         loc=jnp.zeros((channels)), scale=jnp.ones((channels))))
     return b