diff --git a/src/NeuralPDE.jl b/src/NeuralPDE.jl
index 1122afc838..a2ffc2370a 100644
--- a/src/NeuralPDE.jl
+++ b/src/NeuralPDE.jl
@@ -31,7 +31,7 @@ using DomainSets: Domain, ClosedInterval, AbstractInterval, leftendpoint, righte
 using SciMLBase: @add_kwonly, parameterless_type
 using UnPack: @unpack
 import ChainRulesCore, Lux, ComponentArrays
-using Lux: FromFluxAdaptor
+using Lux: FromFluxAdaptor, recursive_eltype
 using ChainRulesCore: @non_differentiable
 
 RuntimeGeneratedFunctions.init(@__MODULE__)
diff --git a/src/ode_solve.jl b/src/ode_solve.jl
index 64d7b3ac6c..bcf9c68ebe 100644
--- a/src/ode_solve.jl
+++ b/src/ode_solve.jl
@@ -370,8 +370,7 @@ function SciMLBase.__solve(prob::SciMLBase.AbstractODEProblem,
     !(chain isa Lux.AbstractExplicitLayer) &&
         error("Only Lux.AbstractExplicitLayer neural networks are supported")
     phi, init_params = generate_phi_θ(chain, t0, u0, init_params)
-    ((eltype(eltype(init_params).types[1]) <: Complex ||
-      eltype(eltype(init_params).types[2]) <: Complex) &&
+    (recursive_eltype(init_params) <: Complex &&
      alg.strategy isa QuadratureTraining) &&
         error("QuadratureTraining cannot be used with complex parameters. Use other strategies.")