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There are a number of important molecular and scientific models that I would love to see implementations for in DeepChem. Implementations of any of these models would be a great contribution to DeepCh…
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Hello everyone!
I'm trying to model highly oscillatory functions ( like the 2D wave function with a source point) via using FNNs, but I can only get limited accuracy despite using numerous approach…
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```julia
deeponet = NeuralOperators.DeepONet(
Chain(
Dense(1 => 10, Lux.tanh_fast), Dense(10 => 10, Lux.tanh_fast), Dense(10 => 10)),
Chain(Dense(1 => 10, Lux.tanh_fast), Dense(10 …
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### Description
The table looks strange on the top left
### (Optional:) Please add any files, screenshots, or other information here.
_No response_
### (Required) What is this issue most closely r…
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Message from Vignesh:
> I think I have chanced upon a very interesting bug. So I am doing some ML training on CSD3 and due to the size of these models and the datasets I end up not having sufficien…
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I modified both `main()` and `ode_system()` as stated in the instructions, but I get a very high test loss. Do I have to modify other functions? I also increased the number of epochs to 10^5 as point…
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```julia
u = ones(Float32, 10, 10, 5)
v = ones(Float32, 1, 10, 5)
deeponet = DeepONet(; branch = (10, 10, 10), trunk = (1, 10, 10))
ps, st = Lux.setup(Random.default_rng(), deeponet)
y, st_ = d…
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Hi again :)
I'd like to bring up a topic that's been keeping me busy lately in the field of Physics-Informed Neural Networks (PINNS). During research I've come across a number of papers that discus…
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Currently, we implement the DeepONet with fully connected networks for branch and trunk. Depending on the problem, one would like to replace these networks by more appropriate ones (e.g. CNNs as branc…
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**Describe the bug**
When trying to train a neural network on the GPU, I'm getting the error message:
[ Info: Training on GPU
[ Info: Start Training
**ArgumentError: cannot take the CPU address…