diff --git a/test/neural_ode_mm_tests.jl b/test/neural_ode_mm_tests.jl
index 964ea42e9..3e437ac9c 100644
--- a/test/neural_ode_mm_tests.jl
+++ b/test/neural_ode_mm_tests.jl
@@ -46,5 +46,5 @@
     optprob = Optimization.OptimizationProblem(optfunc, p)
     res = Optimization.solve(
         optprob, BFGS(; initial_stepnorm = 0.001); callback = cb, maxiters = 100)
-    @test res.minimum < l1
+    @test res.objective < l1
 end
diff --git a/test/newton_neural_ode_tests.jl b/test/newton_neural_ode_tests.jl
index 62e429237..414ccca77 100644
--- a/test/newton_neural_ode_tests.jl
+++ b/test/newton_neural_ode_tests.jl
@@ -27,7 +27,7 @@
     # KrylovTrustRegion is hardcoded to use `Array`
     psd, psax = getdata(ps), getaxes(ps)
 
-    loss_function(θ) = sum(abs2, y .- stnODE(x, ComponentArray(θ, psax))[end])
+    loss_function(θ) = sum(abs2, y .- stnODE(x, ComponentArray(θ, psax)).u[end])
     l1 = loss_function(psd)
     optf = Optimization.OptimizationFunction(
         (x, p) -> loss_function(x), Optimization.AutoZygote())