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Pseudo random numbers can be generated quickly, when you need a lot of them. May be useful for Procedural generation or Monte Carlo simulation.
### haskell/random
#### High level
- [ ] [Ran…
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Sooner or later I'll have to submit to the numbercrunchers and accomodate finer control over the used RNG.
Simple implementation: Add a new root config dict `rng` to the config tree that can contai…
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### 🚀 The feature, motivation and pitch
Hello there,
The vast majority of PyTorch methods support batched inputs and outputs. However, the random generators are left behind in this regard! This …
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[boost random number generators](https://www.boost.org/doc/libs/1_66_0/doc/html/boost_random/reference.html#boost_random.reference.distributions) are probably going to be better than mine quite often.…
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```go
func Int32() int32
func Int32Between(min, max int32) int32
func Int64() int64
func Int64Between(min, max int64) int64
func Uint32() uint32
func Uint32Between(min, max uint32) uint32
…
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Awesome project @RemyLau, thanks for sharing your work on it!
Is there a way to seed the embedding functions/classes so that they produce the same results every time? I didn't see anything to that…
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See if the technique proposed [here](http://csharphelper.com/blog/2014/08/use-a-cryptographic-random-number-generator-in-c/) is more random than Random.
dutts updated
8 years ago
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there's a plethora of pseudo-random number generators PRNGs to choose from. I have used Marsaglia's xorshift:32 before but it's worthwhile to explore this aspect in more detail to find PRNGs suitable …
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Is it ok to use Math.random() directly?
The concern is a potential lack of repeatability because one test's use of the random state will affect the random state observed by tests run later.