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## summary
We've been thinking about how `gh at verify` works. We've realized that `gh at verify` is in effect used to evaluate policy – and that therefore we have to improve its user experience.
As…
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Hi rangers
In gradient boosting machines implementations for *regression problems*, there is usually the possibility to specify *monotonicity constraints* on the impact of the predictors. This can …
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Monotonicity constraint is super useful when you have certain domain knowledge that "all else equal, a higher value in feature X should increase or decrease output Y". This is implemented in most fram…
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In 1D GE models, a monotonic I-spline is used to map from the latent space to the output space. In a GGE model, the moral equivalent of this is to stipulate each output dimension in **y** is monotonic…
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Based on Hyunsu's last question, I elaborated that part on the slides a bit. See page 18.
- If failure is not monotone (i.e., a super input of a failure input makes success), a 1-minimal solution m…
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Often when economists use neural networks, they have theoretical restrictions on the shape:
Monotonically increasing
Concave etc
is this possible in Flux?
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The current suite of tests for the class `Material()`, included in the file _test_material.py_, covers only some of the possible class capabilities.
- In `test_material_from_coeff()` and `test_mate…
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Something I've been thinking about with expansion of library: a decent amount of the work we've been using involves application of inductive biases and teacher-prompted training to model architecture.…
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Assuming strict monotonicity seems quite limiting as it means the backend has to be much more complex.
Can we change pagination to support loose monotonicity, so that the display order is not entir…
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The specification README lists many packages that are not compliant with stated specifications.
Regardless of your feelings on monotonicity (#11, #40, etc), the current spec *claims* ULIDs provide …