Gtifn

12 ms·

1.
Current state of dropout as bayesian approximation(reddit.com)
3 points by Gtifn 9y ago|0 comments
2.
by Gtifn 9y ago
https://fluxml.github.io/ In julia
3.
by Gtifn 9y ago
Julia: https://fluxml.github.io/
4.
Business model/plan(ing) for research heavy early stage ML startup
1 points by Gtifn 9y ago|1 comments
5.
by Gtifn 9y ago
What do you think about a bayesian interpretation of the above as MAP/MLE? https://arxiv.org/abs/1706.00473
6.
by Gtifn 9y ago
cool! How's the performance?
7.
by Gtifn 9y ago
Are you talking about breaking modules (like linalg) out of base or changing the semantics and mechanics of modules? I think the former is planned before 1.0? If the latter, what do you think is the issue? Do you not like julia packages are
8.
by Gtifn 9y ago
What languages do you use?
9.
by Gtifn 9y ago
Just for biotech?
10.
by Gtifn 11y ago
Thanks very much for your thoughts. What do you think about the foundational tech of numba itself? Do you think it is any more of a black box than say Julia? Is there anything about it that would impede extension into a more stable, predic
11.
by Gtifn 11y ago
As a former member of the Numba team, what is your outlook on the technology and the broader continuum ecosystem? I'm looking at Numba and friends (Dynd, blaze) for a new stack, but I'm not sure where the development arc will en
12.
by Gtifn 11y ago
I think distributed's scheduler has seen much iteration since then and is now based on tornado. I wonder if that changes your assessment. Also what do you think of Julia's native distributed capabilities and this library here: ht
13.
by Gtifn 11y ago
How about dask's distrubted array? Do you know how the architecture and goals compare to Elemental?