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  Thanks to everyone who boosted and spread this message. It really means a lot to me!

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  Anybody ever wish their training dashboard was like a video game where you could interactively, during training, increase/decrease their learning rate, batch size, or some other hyperparameter?

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  I wish pytorch just copied the jax vmap functionality instead of went with the "heavily-inspired" line

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  Not enough people are doing prior predictive checks in their Bayesian modeling workflow and it shows!

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  The curse of being able to read a paper and know at a glance which plotting software they used to make their figures. Then drawing spurious inferences about the authors because of it.

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  My lodging plans for #xoxofest fell through. Does anybody know of someone with couch space for a few days?

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  Numpy's broadcast rules are weird as hell, and the scientific python ecosystem is basically stuck with them. If you are building one for another language don't use dim size of 1 for broadcasting but find a non-numeric way to dictate shape.

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  A major reason lots of people don't like eDSLs is that many of them don't have good debugging and other tooling. And it makes sense, you make an eDSL so you can lean on the host language. But, many of them end up being a miserable user experience since use that as license to not add lots of niceties people expect from languages these days.

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  Does anyone have a sense for why Determinantal Point Processes didn't take off? Did another approach for diverse recommendations work better?

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  Hey @thaodan I noticed you were having the same issue as me getting i3 to run under KDE Plasma 6.5 How do I build your forked repo to get your fix running?