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Hello,
I would like to implement a neural network, where I pass kernels to the layers, that then perform a linear combination of the kernels or multiplication. The procedure is described in this pap…
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Implementing the Neural Tangent Kernel adaptive loss method proposed in the "When and Why PINNs Fail to Train: A Neural Tangent Kernel Perspective" [paper](https://arxiv.org/pdf/2007.14527.pdf) by Sif…
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Relates to [this issue](https://github.com/HamletWantToCode/GPFlux.jl/issues/2).
A MWE an be found in the `examples` directory on [this branch](https://github.com/willtebbutt/Stheno.jl/tree/wct/flu…
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### Search before asking
- [X] I have searched the YOLOv5 [issues](https://github.com/ultralytics/yolov5/issues) and [discussions](https://github.com/ultralytics/yolov5/discussions) and found no simi…
Vin-G updated
3 weeks ago
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In OneDNN with Low precision datatype, we have support for u8s8s8 datatype. In Bestla Benchmark Infra we can find couple of classes for low precision types that includes (u8s8s32, s8s8s32 and some cla…
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Hello,
I implemented a brutally simple infinite-width model, calling the kernel_fn with a batch of a single vector.
When I run this on CPU, I don't run into any exorbitant memory issues.
How…
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Tree explainer has the parameter "model_output" using which the models loss can be monitored. Is it possible to do the same for kernel explainer for a neural network model?
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Hello! I was wondering if it's possible for one to write their own `kernel_fn` in neural tangents to do regular kernel regression (for example, a Gaussian kernel). Naively just writing a `new_kernel_f…
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Can we use neural tangent kernel [1] to get the benefits of new neural net architectures while using the budgeted kernel machines? See also the paper on the path kernel [2].
The kernel needs to com…
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# Quanta | science, reflection, projects
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[https://xyli1905.github.io/2019/08/neural-tangent-kernel-and-nn-dynamics/](https://xyli1905.github.io/2019/08/neural-tangent-kernel-and-nn-dynamic…