diff --git a/.buildkite/pipeline.yml b/.buildkite/pipeline.yml
index b96c8e1aaf..26668b555a 100644
--- a/.buildkite/pipeline.yml
+++ b/.buildkite/pipeline.yml
@@ -20,7 +20,6 @@ steps:
     matrix:
       setup:
         version:
-          - "1.6"
           - "1"
         group:
           - "NNODE"
diff --git a/.github/workflows/CI.yml b/.github/workflows/CI.yml
index 0e65682df6..866d6547c9 100644
--- a/.github/workflows/CI.yml
+++ b/.github/workflows/CI.yml
@@ -21,7 +21,6 @@ jobs:
           - Forward
         version:
           - "1"
-          - "1.6"
     steps:
       - uses: actions/checkout@v4
       - uses: julia-actions/setup-julia@v1
diff --git a/Project.toml b/Project.toml
index a544d3318f..5cbe9bedd8 100644
--- a/Project.toml
+++ b/Project.toml
@@ -57,7 +57,7 @@ Flux = "0.13, 0.14"
 ForwardDiff = "0.10"
 Functors = "0.4"
 Integrals = "3.1"
-IntegralsCubature = "0.2"
+IntegralsCubature = "=0.2.2"
 LogDensityProblems = "2"
 Lux = "0.4, 0.5"
 MCMCChains = "6"
diff --git a/docs/Project.toml b/docs/Project.toml
index e136596981..a0da3777ee 100644
--- a/docs/Project.toml
+++ b/docs/Project.toml
@@ -24,7 +24,7 @@ Documenter = "0.27"
 DomainSets = "0.6"
 Flux = "0.13, 0.14"
 Integrals = "3.3"
-IntegralsCubature = "0.2"
+IntegralsCubature = "=0.2.2"
 Lux = "0.4, 0.5"
 ModelingToolkit = "8.33"
 NeuralPDE = "5.3"
diff --git a/docs/src/examples/Lotka_Volterra_BPINNs.md b/docs/src/examples/Lotka_Volterra_BPINNs.md
index f8a8739acf..a61b1a4882 100644
--- a/docs/src/examples/Lotka_Volterra_BPINNs.md
+++ b/docs/src/examples/Lotka_Volterra_BPINNs.md
@@ -60,7 +60,7 @@ To make the example more realistic we add random normally distributed noise to t
 
 
 ```julia
-# Dataset creation for parameter estimation(30 percent noise)
+# Dataset creation for parameter estimation (30% noise)
 time = solution.t
 u = hcat(solution.u...)
 x = u[1, :] + (0.3 .*u[1, :]).*randn(length(u[1, :]))
@@ -88,8 +88,7 @@ alg1 = NeuralPDE.BNNODE(chainflux,
         Normal(2, 2),
         Normal(2, 2),
         Normal(0, 2),
-    ],
-    n_leapfrog = 30, progress = true)
+    ], progress = true)
 
 sol_flux_pestim = solve(prob, alg1)
 
@@ -98,7 +97,7 @@ alg2 = NeuralPDE.BNNODE(chainlux,
     draw_samples = 1000,
     phystd = [0.05, 0.05],
     priorsNNw = (0.0, 10.0),
-    n_leapfrog = 30, progress = true)
+    progress = true)
 
 sol_lux = solve(prob, alg2)