diff --git a/CHANGELOG.md b/CHANGELOG.md
index d48bfb526..2ae90818b 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -41,6 +41,7 @@ Entries link to the pull request that introduced them.
 ## GraphNeuralNetworks.jl — Unreleased (towards 1.1.1)
 
 **Changed**
+- `GNNRecurrence` now hands each cell an indexed time slice instead of an `eachslice` view, matching the Lux frontend. Enzyme's type analysis fails on `SubArray` cell inputs, so this unblocks `DCGRU`, `EvolveGCNO`, `GConvGRU` and `GConvLSTM` under Enzyme ([#707]).
 - The recurrent temporal cells now delegate their forward-pass math to shared `GNNlib` functions (requires GNNlib ≥ 1.4); the layer behaviour is unchanged ([#696]).
 
 ## GNNlib.jl 1.4.0 — 2026-07-22
@@ -235,5 +236,6 @@ Lux implementations of the graph convolutional, pooling, and temporal layers
 [#696]: https://github.com/JuliaGraphs/GraphNeuralNetworks.jl/pull/696
 [#703]: https://github.com/JuliaGraphs/GraphNeuralNetworks.jl/pull/703
 [#704]: https://github.com/JuliaGraphs/GraphNeuralNetworks.jl/pull/704
+[#707]: https://github.com/JuliaGraphs/GraphNeuralNetworks.jl/pull/707
 [#706]: https://github.com/JuliaGraphs/GraphNeuralNetworks.jl/pull/706
 [FluxML/Zygote.jl#1662]: https://github.com/FluxML/Zygote.jl/issues/1662
diff --git a/GraphNeuralNetworks/src/layers/temporalconv.jl b/GraphNeuralNetworks/src/layers/temporalconv.jl
index 347c8ff7a..e6b895a8f 100644
--- a/GraphNeuralNetworks/src/layers/temporalconv.jl
+++ b/GraphNeuralNetworks/src/layers/temporalconv.jl
@@ -1,7 +1,9 @@
 function scan(cell, g::GNNGraph, x::AbstractArray{T,3}, state) where {T}
     y = []
-    for xt in eachslice(x, dims = 2)
-        yt, state = cell(g, xt, state)
+    for t in 1:size(x, 2)
+        # slice by indexing, not `eachslice`: Enzyme's type analysis fails on
+        # `SubArray` cell inputs. The Lux frontend slices the same way.
+        yt, state = cell(g, x[:, t, :], state)
         y = vcat(y, [yt])
     end
     return stack(y, dims = 2)