[09x09] bayesian deep learning through laplace's approximation using laplaceredux.jl and flux.jl
Published 1 year ago • 1.5K plays • Length 30:33Download video MP4
Download video MP3
Similar videos
-
24:57
[05x08] intro to artificial neural networks with flux.jl (1 of 2); julia supervised machine learning
-
30:53
[09x08] intro to bayesian differential equations using ordinarydiffeq.jl and turing.jl
-
4:16
building deep learning models in flux.jl (4 minute tour)
-
20:59
juliacon 2020 | geometricflux.jl: geometric deep learning on flux | yueh-hua tu
-
26:50
neural networks using lux.jl and zygote.jl autodiff in julia
-
23:35
[09x05] bayesian b-splines | bsplines.jl & turing.jl | cherry tree flowering in kyoto city by year
-
25:45
[09x10] intro to rxinfer.jl | automatic bayesian inference on factor graph with message passing
-
25:49
scaling up training of any flux.jl model made easy | dhairya gandhi | juliacon 2022
-
1:35
why flux? the elegant julia machine learning library
-
36:22
learning flux.jl from a tensorflow background | talk julia #9