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Please consider supporting "soft" decision tree ensembles like those in the SoftBart R package. That seems pretty on-point as a smoothing technique which would be exciting to have in a distributional …
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Hi, what does the "u" means in the following code snippets? It seems that the "u" is not defined in the code? Thanks!
huber_loss = 0.5 * u.abs().clamp(min=0.0, max=k).pow(2)
huber_loss += k *…
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Nice package, I have been looking for methods for heteroskedastic distribution prediction! (see https://github.com/sktime/skpro/issues/7)
More generally, I think `rolch` would fit the scope of skpr…
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I am a bit confused how the correlation of ZOS and thermal expansion is defined in `tlm_sterodynamics_fit_oceandynamics.py `:
https://github.com/radical-collaboration/facts/blob/3ff08f91a8d8180b705…
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- Matern covariance functions for GP effects / trends
- 2d FFT GPs (or even 1d) for complex but stationary GP effects (https://arxiv.org/pdf/2301.08836.pdf)
- Multivariate normal observation models
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In [Distributional Reinforcement Learning with Quantile Regression](https://arxiv.org/pdf/1710.10044.pdf), they propose a testing environment where wind is added to the environment to make a gridworld…
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Hi guys!
As distributional analysis is becoming more common in development economics and in policy evaluation in general (see, e.g., http://documents.worldbank.org/curated/en/292901499351272899/Dis…
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It would be nice to have an option to use randomized quantile residuals (i.e. from `statmod::qresid()`) in `appraise()`. Maybe this could even be the default for poisson and binomial models? Accordi…
Aariq updated
3 months ago
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First, hands down, amazing work. Serving as a baseline, I see a possible improvement, if someone wants to implement it:
- The n-step return, as it is, is biased (as you are using old off-policy sam…
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Dear Authors,
I found your paper interesting and had a question. For the distributional critic, why is the number of quantiles (51 as reported) not equal to the noise vector dimension (5 as report…