Questions tagged [uncertainty-quantification]

For questions about uncertainty quantification (aka uncertainty estimation) in the context of artificial intelligence, in particular, in the context of Bayesian machine learning.

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Why would the "improvement" be the result of random initialization, and so why should we use multiple runs?

I got this feedback for my thesis paper. The improvement shown in the results section could be the result of random initialization. There should be multiple runs with means and standard deviations. ...
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Does MobileNet SSD v2 only capture aleatoric uncertainty (and so not the epistemic one)?

Regarding the MobileNet SSD v2 model, I was wondering to what extend it captures uncertainty of the predictions. There are 2 types of uncertainty, data uncertainty (aleatoric) and model uncertainty (...
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What are the standard ways to measure the quality of a set of numerical predictions that include uncertainties?

I have a radial basis function that supplies uncertainties (standard deviations) with its predictions, which are numerical values. This function is computed for a particular point by computing its ...
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Do we need as much information to know if we can can answer a question as we need to actually answer the question?

I am reading The Book of Why: The New Science of Cause and Effect by Judea Pearl, and in page 12 I see the following diagram. The box on the right side of box 5 "Can the query be answered?" ...
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How were the pictures for Geo-reCAPTCHA selected?

I learned from this site that reCAPTCHA is utilized as a method to digitize distorted characters by offer an unknown one and a known one. Much like a Mechanical Turk application, ReCaptcha uses ...
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Why does this formula $\sigma^2 + \frac{1}{T}\sum_{t=1}^Tf^{\hat{W_t}}(x)^Tf^{\hat{W_t}}(x_t)-E(y)^TE(y)$ approximate the variance?

How does: $$\text{Var}(y) \approx \sigma^2 + \frac{1}{T}\sum_{t=1}^Tf^{\hat{W_t}}(x)^Tf^{\hat{W_t}}(x_t)-E(y)^TE(y)$$ approximate variance? I'm currently reading What Uncertainties Do We Need in ...
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How can I use Monte Carlo Dropout in a pre-trained CNN model?

In Monte Carlo Dropout (MCD), I know that I should enable dropout during training and testing, then get multiple predictions for the same input $x$ by performing multiple forward passes with $x$, then,...
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Why is my Keras prediction always close to 100% for one image class?

I am using Keras (on top of TF 2.3) to train an image classifier. In some cases I have more than two classes, but often there are just two classes (either "good" or "bad"). I am ...
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Is there any research on models that provide uncertainty estimation?

Is there any research on machine learning models that provide uncertainty estimation? If I train a denoising autoencoder on words and put through a noised word, I'd like it to return a certainty that ...