Question

Efficiently fill an array from a function

score 1.4k · Answer 1 · 2024-12-25 01:05:19

1.4k

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Efficiently fill an array from a function

Published on 25 December 2024 at 01:05

score 4.3k · Answer 2 · 2024-12-29 07:05:22

4.3k

Views

Conditional update in JAX?

Published on 29 December 2024 at 07:05

score 221 · Answer 3 · 2024-12-25 01:03:29

221

Views

Alternative to scipy stats zmap function

Published on 25 December 2024 at 01:03

score 112 · Answer 4 · 2024-12-30 22:45:32

112

Views

Installing Jax on Fedora 38

Published on 30 December 2024 at 22:45

score 76 · Answer 5 · 2024-12-25 01:11:52

76

Views

Are PINNs inherently worse at solving 2nd-order PDEs?

Published on 25 December 2024 at 01:11

score 115 · Answer 6 · 2024-12-25 01:08:18

115

Views

how to make hashable datatype to use with jit?

Published on 25 December 2024 at 01:08

score 139 · Answer 7 · 2024-12-25 01:03:29

139

Views

better way to use lax.cond, partial, vmap

Published on 25 December 2024 at 01:03

score 208 · Answer 8 · 2024-12-25 01:18:25

208

Views

Why does jnp.einsum produce a different result from manual looping?

Published on 25 December 2024 at 01:18

score 211 · Answer 9 · 2024-12-25 01:10:03

211

Views

vectorized minimization and root finding in jax

Published on 25 December 2024 at 01:10

score 175 · Answer 10 · 2024-12-25 01:09:26

175

Views

Appending to list alternative workflow for JAX

Published on 25 December 2024 at 01:09

score 76 · Answer 11 · 2024-12-25 01:18:25

76

Views

how to use jit with control flow and arrays without slowing down

Published on 25 December 2024 at 01:18

score 83 · Answer 12 · 2024-12-25 01:01:41

83

Views

Cross dimensional segmented operation

Published on 25 December 2024 at 01:01

score 212 · Answer 13 · 2024-12-25 01:27:35

212

Views

Why matrix multiplication results with JAX are different if the data is sharded differently on the GPU

Published on 25 December 2024 at 01:27

score 173 · Answer 14 · 2024-12-25 01:13:46

173

Views

Idiomatic ways to handle errors in JAX jitted functions

Published on 25 December 2024 at 01:13

score 2.1k · Answer 15 · 2024-12-25 01:05:17

2.1k

Views

CUDA and JAX libraries are not compatible

Published on 25 December 2024 at 01:05

score 266 · Answer 16 · 2024-12-29 07:45:24

266

Views

PyTorch autograd: Efficient computation of Jacobian and Jacobian-Vector-product of scalar function over range of inputs

Published on 29 December 2024 at 07:45

score 168 · Answer 17 · 2024-12-25 01:05:16

168

Views

Convert for loop to jax.lax.scan

Published on 25 December 2024 at 01:05

score 204 · Answer 18 · 2024-12-25 01:00:07

204

Views

JAX vmap JIT behind the scenes?

Published on 25 December 2024 at 01:00

score 265 · Answer 19 · 2024-12-25 01:00:37

265

Views

JAX @jit for nested class method

Published on 25 December 2024 at 01:00

score 91 · Answer 20 · 2024-12-25 01:18:24

91

Views

Mapping over multiple functions in JAX to speed up for loops

Published on 25 December 2024 at 01:18

List Question

Efficiently fill an array from a function

Conditional update in JAX?

Alternative to scipy stats zmap function

Installing Jax on Fedora 38

Are PINNs inherently worse at solving 2nd-order PDEs?

how to make hashable datatype to use with jit?

better way to use lax.cond, partial, vmap

Why does jnp.einsum produce a different result from manual looping?

vectorized minimization and root finding in jax

Appending to list alternative workflow for JAX

how to use jit with control flow and arrays without slowing down

Cross dimensional segmented operation

Why matrix multiplication results with JAX are different if the data is sharded differently on the GPU

Idiomatic ways to handle errors in JAX jitted functions

CUDA and JAX libraries are not compatible

PyTorch autograd: Efficient computation of Jacobian and Jacobian-Vector-product of scalar function over range of inputs

Convert for loop to jax.lax.scan

JAX vmap JIT behind the scenes?

JAX @jit for nested class method

Mapping over multiple functions in JAX to speed up for loops

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