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This paper might be relevant: https://arxiv.org/abs/2111.10144
To quote the abstract:
> Graph neural networks (GNNs) provide a powerful and scalable solution for modeling continuous spatial data…
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I can see two issues in the way the Nataf transformation is defined In Transformation.py:
* The Nataf transformation is presented as a way to induce correlation between random variables, which is not…
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Hi , first not very sure that the issues section is the best place for this so I apologise before hand. Theres not much of a forum community online for JAX (no mailing list ?) yet, and this can almost…
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Training new neural networks currently involves making decisions given the following parameters [1]:
- training window
- learning rate
- number of trainingsteps
- batch size
- train/test ratio
…
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I am thinking about the high level design of this package and came up with this:
```mermaid
flowchart LR
subgraph "Models"
subgraph "Physics"
subgraph "Analytical"
harmonic_oscillato…
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In the original implementation, there is reference that Gibbs kernel is only supported for 1d inputs.
https://github.com/pymc-devs/pymc/blob/f67ff8bc22fcc72ead96eeeaef04173ed53650cb/pymc/gp/cov.py#L8…
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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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2개의 용어는 둘다 정확도를 높여주고 최적의 값들을 찾아주는 기법 (similar to convex from Ernest)
이 2개의 기법의 연관성과 같이 결합하여 사용할수 있는지를 조사해보기
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Hello Jan,
Glad to discover by accident your gp_extras which appear to deal, based on sklearn, with the same issues as "Nested Variational Compression in Deep Gaussian Processes" by James Hensman and…
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Looking at the tutorials, the ordering looks a bit random. Perhaps we should reorder the tutorials, roughly in order from least to most advanced, to make it easier to understand them? I'd suggest some…