Kenta Sato
Kenta Sato
I tried to compute the gradient of a function with quadratic form. However, it failed with ambiguity error as follows: ```julia import ReverseDiff const A = [1.0 2.0; 2.0 5.0]...
The docstring of `ReverseDiff.@forward` says: > Currently, only `length(args) 3 arguments: ``` julia> import ReverseDiff julia> ReverseDiff.@forward f(x, y, z, w) = x + 2y + 3z + 4w ReverseDiff.ForwardOptimize{##hidden_f}(#hidden_f)...
This implements `std` for multivariate distributions as an element-wise square root of variance: `std(d) = sqrt.(var(d))`.
Hi, I tried to serialize an object with a type parameter and deserialize it from a BSON file. However, it doesn't work because BSON.jl cannot recover the parameter type in...
See: https://github.com/JuliaDebug/JuliaInterpreter.jl/pull/484
This behavior is surprising because it suddenly jumps to an unexpected place: ``` julia> function foo(x) println(x) y = 0 if x y = 1 end return y end foo...
This PR makes the next command less skipping. The motivation is described here: https://github.com/JuliaDebug/Debugger.jl/issues/291. ~~My approach is to add a keyword argument (`sameline`) to the `maybe_next_call!` function so that it...
Supercedes #7.
Some of these changes will need features introduced in Julia 1.0. ## Properties - Add node properties: `type`, `path`, `name`, `content`, `namespace` (#54). - Add document properties: `root`, `dtd` (#54)....