-
Thank you for your great work! I have a question: Are neural operators suitable for solving inverse problems like image denoising?
-
We need to compare with
1. Old `NeuralOperators.jl`
2. Pytorch Neural Operators https://github.com/neuraloperator/neuraloperator
3. Some Jax version?
cc @ayushinav let's prioritize this
-
Implement Convolutional Neural Operators:
- https://arxiv.org/abs/2302.01178
- https://github.com/bogdanraonic3/ConvolutionalNeuralOperator
In this task, we could also implement standard U-…
-
## Feature request
Request the implementation of the following ONNX operators:
* LogSoftmax
* Softmax
* ReduceMax
## Motivation
These operators are common in neural networks of many types;…
-
-
What was the grid-resolution of dataset that was used for shape-net car and Ahmed body CFD example in this paper (https://arxiv.org/pdf/2307.15034). I am wokring with `torch==2.0.1+cu117'` and it look…
-
### Description
ONNX (Open Neural Network Exchange) provides cross-platform compatibility
An operator that can run inference using ONNX models, ideal for deploying machine learning models in a …
-
In GitLab by @corepointer on Mar 18, 2022, 11:31
We have most of our neural network operators (convolutions et al) implemented as calls to
cuDNN. An initial (pooling) operator is ported from SystemDS…
-
Couple of strategy/scenarios
1) train-to-train model
- train a sub-class of PDEs with NeuralOperator
- transfer learning pre-trained prediction from NeuralOperator problem to PINNs
- PINNs train…
-
### Expected behavior
The PL operator arithmetic allows for operators with imaginary/complex coefficients. If such expectation values of such operators are measured I expect to either get a imaginar…
cvjjm updated
2 weeks ago