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docs/src/index.md

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@@ -109,4 +109,4 @@ opt = ADAM(learning_rate)
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parameters = params(model)
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Flux.@epochs 400 Flux.train!(loss, parameters, [(xtrain,ytrain,grid)], opt, cb = evalcb)
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```
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A more complete example using DeepONet architecture to solve Burgers can be found in the [examples]()
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A more complete example using DeepONet architecture to solve Burgers' equation can be found in the [examples](../../example/Burgers/src/Burgers_deeponet.jl)

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