# Machine Learning

**URL:** https://discourse.julialang.org/c/domain/ml/24.md?page=1

[Latest](https://discourse.julialang.org/latest.md) · [Categories](https://discourse.julialang.org/categories.md) · [Tags](https://discourse.julialang.org/tags.md)

**Page:** 2

---

## [Julia Flux Deep Learning Examples](https://discourse.julialang.org/t/julia-flux-deep-learning-examples/135788)

<div class="topic-metadata">

**Author:** [@Stergios\_Papadimitri](https://discourse.julialang.org/u/Stergios_Papadimitri)\
**Replies:** 0\
**Last updated:** [February 23, 2026, 11:48am UTC](https://discourse.julialang.org/t/julia-flux-deep-learning-examples/135788 "2026-02-23T11:48:04Z")

</div>

I created the project github dot com slash sterg24 slash JuliaDeepLearningFluxExamples that aims to develop good examples of deep learning with the Flux Julia’s framework

---

## [How to install Pytorch with cuda support through CondaPkg](https://discourse.julialang.org/t/how-to-install-pytorch-with-cuda-support-through-condapkg/135690)

<div class="topic-metadata">

**Author:** [@Tomas\_Pevny](https://discourse.julialang.org/u/Tomas_Pevny)\
**Replies:** 4\
**Last updated:** [February 18, 2026, 5:25am UTC](https://discourse.julialang.org/t/how-to-install-pytorch-with-cuda-support-through-condapkg/135690 "2026-02-18T05:25:12Z")

</div>

Hi All, I would like to ask, if anyone knows how to install pytorch with cuda support through CondaPkg. It has to happen that I need to call some language models and I have opted to use transformers from HuggingFace, as…

---

## [Saving an Echo State Network (ReservoirComputing.jl)](https://discourse.julialang.org/t/saving-an-echo-state-network-reservoircomputing-jl/95338)

<div class="topic-metadata">

**Author:** [@monstera](https://discourse.julialang.org/u/monstera)\
**Replies:** 6\
**Last updated:** [January 24, 2026, 6:22pm UTC](https://discourse.julialang.org/t/saving-an-echo-state-network-reservoircomputing-jl/95338 "2026-01-24T18:22:50Z")

</div>

Hi, I am trying to save an Echo State Network (ESN) struct + output Matrix in Julia to load it again in another script to predict a time series. Out of several thousand ESNs, I am choosing the hundred best ones and try …

---

## [How to set seed for Random.TaskLocalRNG()?](https://discourse.julialang.org/t/how-to-set-seed-for-random-tasklocalrng/135236)

<div class="topic-metadata">

**Author:** [@tomtom](https://discourse.julialang.org/u/tomtom)\
**Replies:** 9\
**Last updated:** [January 24, 2026, 5:16pm UTC](https://discourse.julialang.org/t/how-to-set-seed-for-random-tasklocalrng/135236 "2026-01-24T17:16:43Z")

</div>

I see the following: using MLJ Tree = @load DecisionTreeClassifier pkg=DecisionTree julia\> tree = Tree() DecisionTreeClassifier( max\_depth = -1, min\_samples\_leaf = 1, min\_samples\_split = 2, min\_purity\_increase …

---

## [Slow Reactant compilation for modified DeepONet](https://discourse.julialang.org/t/slow-reactant-compilation-for-modified-deeponet/135133)

<div class="topic-metadata">

**Author:** [@Jan\_Strube](https://discourse.julialang.org/u/Jan_Strube)\
**Replies:** 9\
**Last updated:** [January 23, 2026, 8:55pm UTC](https://discourse.julialang.org/t/slow-reactant-compilation-for-modified-deeponet/135133 "2026-01-23T20:55:23Z")

</div>

I’m trying to implement the modified Deep Operator Network from this paper: Improved architectures and training algorithms for deep operator networks" (arXiv:2110.01654). The addition over the vanilla DeepONet is a set …

---

## [Input Convex Neural Network is not Convex at Origin in Lux.jl](https://discourse.julialang.org/t/input-convex-neural-network-is-not-convex-at-origin-in-lux-jl/133565)

<div class="topic-metadata">

**Author:** [@Lizuo\_Liu](https://discourse.julialang.org/u/Lizuo_Liu)\
**Replies:** 2\
**Last updated:** [January 18, 2026, 5:18pm UTC](https://discourse.julialang.org/t/input-convex-neural-network-is-not-convex-at-origin-in-lux-jl/133565 "2026-01-18T17:18:45Z")

</div>

Hi, I utilize Lux.jl implemented the input convex neural network, but it doesn’t show positive eigenvalues at origin. Below is the working example. Any comment is appreciated. using Lux using Random using LinearAlgebra…

---

## [Reset model parameters Flux.jl](https://discourse.julialang.org/t/reset-model-parameters-flux-jl/35021)

<div class="topic-metadata">

**Author:** [@luboshanus](https://discourse.julialang.org/u/luboshanus)\
**Replies:** 3\
**Last updated:** [January 15, 2026, 4:05pm UTC](https://discourse.julialang.org/t/reset-model-parameters-flux-jl/35021 "2026-01-15T16:05:48Z")

</div>

Hi, I’d like to ask how to reset model parameters without saving initial parameters of the model such as init\_theta = Flux.params(model) and then loading them to the model when reseting. I would like to use built in Flu…

---

## [Symposium “PIML Day: Methodological and theoretical advances in Physics-Informed Machine Learning" - Paris 15 April 2026](https://discourse.julialang.org/t/symposium-piml-day-methodological-and-theoretical-advances-in-physics-informed-machine-learning-paris-15-april-2026/134974)

<div class="topic-metadata">

**Author:** [@sylvaticus](https://discourse.julialang.org/u/sylvaticus)\
**Replies:** 2\
**Last updated:** [January 10, 2026, 7:43pm UTC](https://discourse.julialang.org/t/symposium-piml-day-methodological-and-theoretical-advances-in-physics-informed-machine-learning-paris-15-april-2026/134974 "2026-01-10T19:43:53Z")

</div>

Hello, I forward the announcement below: We are pleased to announce the symposium “PIML Day: Methodological and theoretical advances in Physics-Informed Machine Learning” on Wednesday, April 15, 2026. The event will ta…

---

## [NODE Training - Performance w/ Lux vs torchdiffeq](https://discourse.julialang.org/t/node-training-performance-w-lux-vs-torchdiffeq/134860)

<div class="topic-metadata">

**Author:** [@csvance](https://discourse.julialang.org/u/csvance)\
**Replies:** 6\
**Last updated:** [January 5, 2026, 7:13pm UTC](https://discourse.julialang.org/t/node-training-performance-w-lux-vs-torchdiffeq/134860 "2026-01-05T19:13:34Z")

</div>

So I’ve been training a neural ODE in Python using PyTorch and torchdiffeq. I was going to start with Julia and Lux but I ended up needing to train some upstream stuff (pretrained CNN backbones and custom PyTorch layers)…

---

## [Machine Learning and Deep Learning Course with Julia](https://discourse.julialang.org/t/machine-learning-and-deep-learning-course-with-julia/134890)

<div class="topic-metadata">

**Author:** [@rajgoel](https://discourse.julialang.org/u/rajgoel)\
**Replies:** 1\
**Last updated:** [January 5, 2026, 4:13pm UTC](https://discourse.julialang.org/t/machine-learning-and-deep-learning-course-with-julia/134890 "2026-01-05T16:13:47Z")

</div>

I created a course on Machine Learning and Deep Learning that is using Julia and Flux.jl in particular. I wanted the course to be mathematically precise while providing concise implementations that match the notation use…

---

## [Looking for Examples of Symbolic Regression for predicting Hidden Markov Models](https://discourse.julialang.org/t/looking-for-examples-of-symbolic-regression-for-predicting-hidden-markov-models/134749)

<div class="topic-metadata">

**Author:** [@mj2984](https://discourse.julialang.org/u/mj2984)\
**Replies:** 9\
**Last updated:** [December 31, 2025, 2:03am UTC](https://discourse.julialang.org/t/looking-for-examples-of-symbolic-regression-for-predicting-hidden-markov-models/134749 "2025-12-31T02:03:53Z")

</div>

I have a set of time series data that track an observable (o(t)) vs control signal (c(t)) over a period of time. One way I know to model this system is using Recurrent Neural Networks or some variant of it. I am looking …

---

## [Will Reactant.jl become a machine learning framework?](https://discourse.julialang.org/t/will-reactant-jl-become-a-machine-learning-framework/125478)

<div class="topic-metadata">

**Author:** [@Tarny\_GG\_Channie](https://discourse.julialang.org/u/Tarny_GG_Channie)\
**Replies:** 16\
**Last updated:** [December 23, 2025, 8:55pm UTC](https://discourse.julialang.org/t/will-reactant-jl-become-a-machine-learning-framework/125478 "2025-12-23T20:55:00Z")

</div>

I made an observation that MLIR + Enzyme could form quite a capable ML framework, and then, well… like the last time I theorized about how a good language would work, and Julians were one step ahead of me, creating Julia…

---

## [Matrix multiplication fails with Reactant and Lux](https://discourse.julialang.org/t/matrix-multiplication-fails-with-reactant-and-lux/134612)

<div class="topic-metadata">

**Author:** [@weltenbummler](https://discourse.julialang.org/u/weltenbummler)\
**Replies:** 2\
**Last updated:** [December 17, 2025, 4:34pm UTC](https://discourse.julialang.org/t/matrix-multiplication-fails-with-reactant-and-lux/134612 "2025-12-17T16:34:06Z")

</div>

Hello, I have this simple script: using LinearAlgebra using Reactant using Lux dev = reactant\_device() #dev = cpu\_device() A = dev(rand(Float32, 2, 2)) B = dev(rand(Float32, 2, 3)) A \* B # ERROR: conversion to point…

---

## [Learning a mapping from an image to an ODE](https://discourse.julialang.org/t/learning-a-mapping-from-an-image-to-an-ode/134456)

<div class="topic-metadata">

**Author:** [@csvance](https://discourse.julialang.org/u/csvance)\
**Replies:** 4\
**Last updated:** [December 10, 2025, 6:00pm UTC](https://discourse.julialang.org/t/learning-a-mapping-from-an-image-to-an-ode/134456 "2025-12-10T18:00:06Z")

</div>

I have trained a CNN to map an image to a sequence of feature vectors f\_v and I want to learn a function du(u, f\_v) that maps the feature vectors to an ODE. For each image I know how to compute both the function and firs…

---

## [Correctness Issue in NeuralOperators.jl: Mode truncation in SpectralConv excludes negative low-frequency modes](https://discourse.julialang.org/t/correctness-issue-in-neuraloperators-jl-mode-truncation-in-spectralconv-excludes-negative-low-frequency-modes/134403)

<div class="topic-metadata">

**Author:** [@Azamat](https://discourse.julialang.org/u/Azamat)\
**Replies:** 2\
**Last updated:** [December 9, 2025, 8:26am UTC](https://discourse.julialang.org/t/correctness-issue-in-neuraloperators-jl-mode-truncation-in-spectralconv-excludes-negative-low-frequency-modes/134403 "2025-12-09T08:26:17Z")

</div>

I was looking at the mode truncation logic in NeuralOperators.jl and have a question about correctness. Link: NeuralOperators.jl/src/transform.jl at 39f8a3c6dc974e711c8de8a8fde804e096098157 · SciML/NeuralOperators.jl · …

---

## [Using Neural ODEs to learn a family of ODEs (with Automatic Differentiation)](https://discourse.julialang.org/t/using-neural-odes-to-learn-a-family-of-odes-with-automatic-differentiation/134348)

<div class="topic-metadata">

**Author:** [@leespen1](https://discourse.julialang.org/u/leespen1)\
**Replies:** 13\
**Last updated:** [December 9, 2025, 1:59am UTC](https://discourse.julialang.org/t/using-neural-odes-to-learn-a-family-of-odes-with-automatic-differentiation/134348 "2025-12-09T01:59:34Z")

</div>

I am running into issues when trying to use reverse-mode automatic differentiation via Zygote when trying to solve families of Given u(t), we can train a neural ODE to find the underlying ODE du/dt = f(u, t). For examp…

---

## [What is the most ideal predictor for predicting binary vectors?](https://discourse.julialang.org/t/what-is-the-most-ideal-predictor-for-predicting-binary-vectors/134260)

<div class="topic-metadata">

**Author:** [@WuSiren](https://discourse.julialang.org/u/WuSiren)\
**Replies:** 6\
**Last updated:** [December 2, 2025, 3:13pm UTC](https://discourse.julialang.org/t/what-is-the-most-ideal-predictor-for-predicting-binary-vectors/134260 "2025-12-02T15:13:59Z")

</div>

I want to predict a vector whose elements are binary. What is the most promising machine learning model for doing this at present? Is there a corresponding Julia package?

---

## [How to correctly use Lux and Training API with reactant?](https://discourse.julialang.org/t/how-to-correctly-use-lux-and-training-api-with-reactant/133799)

<div class="topic-metadata">

**Author:** [@rkube](https://discourse.julialang.org/u/rkube)\
**Replies:** 3\
**Last updated:** [November 12, 2025, 6:04pm UTC](https://discourse.julialang.org/t/how-to-correctly-use-lux-and-training-api-with-reactant/133799 "2025-11-12T18:04:09Z")

</div>

Hi, I’m trying to train neural networks with Lux, Reactant, and the Training API and am confused about how to tie it together. When I’m compiling a model with reactant, should I still use the TrainState API? I tried …

---

## [Quantile Random Forest in Julia?](https://discourse.julialang.org/t/quantile-random-forest-in-julia/133383)

<div class="topic-metadata">

**Author:** [@allixender](https://discourse.julialang.org/u/allixender)\
**Replies:** 1\
**Last updated:** [November 12, 2025, 4:42am UTC](https://discourse.julialang.org/t/quantile-random-forest-in-julia/133383 "2025-11-12T04:42:11Z")

</div>

Hi there, I have played a bit with DecisionTree.jl and MJL.jl. Now I would like to get some uncertainty quantification for my RandomForest regressions. I have seen that Quantile Random Forest is an increasingly accepte…

---

## [Has anyone tried implementing the LiMuon Optimizer?](https://discourse.julialang.org/t/has-anyone-tried-implementing-the-limuon-optimizer/132742)

<div class="topic-metadata">

**Author:** [@DoktorMike](https://discourse.julialang.org/u/DoktorMike)\
**Replies:** 2\
**Last updated:** [November 7, 2025, 8:33pm UTC](https://discourse.julialang.org/t/has-anyone-tried-implementing-the-limuon-optimizer/132742 "2025-11-07T20:33:54Z")

</div>

Has anyone tried implementing the LiMuon optimizer? I made an issue here in the Optimisers.jl package but thought I’d ask here as well if someone has implemented it elsewhere? Also any hands on experience with the metho…

---

## [Lux/Enzyme error when Training my model?](https://discourse.julialang.org/t/lux-enzyme-error-when-training-my-model/133442)

<div class="topic-metadata">

**Author:** [@rkube](https://discourse.julialang.org/u/rkube)\
**Replies:** 9\
**Last updated:** [November 2, 2025, 1:44am UTC](https://discourse.julialang.org/t/lux-enzyme-error-when-training-my-model/133442 "2025-11-02T01:44:19Z")

</div>

Hi, I’m trying to get a simple language model to train using Lux/Enzyme and get a big scary error. Does anyone have insight into how to get to the bottom of this? Is there an error in the MWE? I tried Zygote and it run…

---

## [Issue: Enzyme + Flux double differentiation on custom layer](https://discourse.julialang.org/t/issue-enzyme-flux-double-differentiation-on-custom-layer/133503)

<div class="topic-metadata">

**Author:** [@Gianmarco](https://discourse.julialang.org/u/Gianmarco)\
**Replies:** 3\
**Last updated:** [October 30, 2025, 1:52am UTC](https://discourse.julialang.org/t/issue-enzyme-flux-double-differentiation-on-custom-layer/133503 "2025-10-30T01:52:28Z")

</div>

Hi, I’m using Flux and Enzyme for a project, and the entire architecture is built on top of these two libraries. So unless strictly necessary, I’d like to stay within the Flux/Enzyme ecosystem. For both libraries i’m u…

---

## [New "easy rule" system for Enzyme](https://discourse.julialang.org/t/new-easy-rule-system-for-enzyme/133522)

<div class="topic-metadata">

**Author:** [@gdalle](https://discourse.julialang.org/u/gdalle)\
**Replies:** 4\
**Last updated:** [October 29, 2025, 9:27pm UTC](https://discourse.julialang.org/t/new-easy-rule-system-for-enzyme/133522 "2025-10-29T21:27:57Z")

</div>

Hi there @wsmoses and friends, Thanks for the new easy rule system! Making rules more accessible is a great idea to get more people into autodiff (that’s how I got hooked in the first place). I’m curious to understand …

---

## [Problems when replacing Flux by Lux in anodes example](https://discourse.julialang.org/t/problems-when-replacing-flux-by-lux-in-anodes-example/133120)

<div class="topic-metadata">

**Author:** [@Jaime\_Araneda](https://discourse.julialang.org/u/Jaime_Araneda)\
**Replies:** 1\
**Last updated:** [October 24, 2025, 1:19pm UTC](https://discourse.julialang.org/t/problems-when-replacing-flux-by-lux-in-anodes-example/133120 "2025-10-24T13:19:21Z")

</div>

Hello, I’m trying to reproduce the anodes example on augmented neural ODEs from the thread Fitting neural ODE to periodic time series. However, when replacing Flux by the Lux library (with the corresponding changes) I g…

---

## [How to ignore minibatches with NaN gradients optimizing a hybrid LUX model using Optimization.jl](https://discourse.julialang.org/t/how-to-ignore-minibatches-with-nan-gradients-optimizing-a-hybrid-lux-model-using-optimization-jl/132615)

<div class="topic-metadata">

**Author:** [@progtw1](https://discourse.julialang.org/u/progtw1)\
**Replies:** 1\
**Last updated:** [October 24, 2025, 1:17pm UTC](https://discourse.julialang.org/t/how-to-ignore-minibatches-with-nan-gradients-optimizing-a-hybrid-lux-model-using-optimization-jl/132615 "2025-10-24T13:17:45Z")

</div>

I try following the LUX tutorial on fitting an ML model using Optimization.jl for fitting a hybrid model, where the LUX model predicts some parameters of a process-based model, the LUX model application is just a call in…

---

## [Best options for Graph Neural Network integration with Flux](https://discourse.julialang.org/t/best-options-for-graph-neural-network-integration-with-flux/133368)

<div class="topic-metadata">

**Author:** [@AriMarkowitz](https://discourse.julialang.org/u/AriMarkowitz)\
**Replies:** 5\
**Last updated:** [October 24, 2025, 7:15am UTC](https://discourse.julialang.org/t/best-options-for-graph-neural-network-integration-with-flux/133368 "2025-10-24T07:15:42Z")

</div>

Hello! I built a library that utilizes GraphNeuralNetworks.jl and Flux.jl, but the GraphNeuralNetworks.jl tests are currently failing in Julia 1.12 (and the same failure is causing my custom library to crash when used).…

---

## [Lotka Volterra Neural ODE](https://discourse.julialang.org/t/lotka-volterra-neural-ode/133159)

<div class="topic-metadata">

**Author:** [@Aditya\_Deshpande](https://discourse.julialang.org/u/Aditya_Deshpande)\
**Replies:** 5\
**Last updated:** [October 19, 2025, 9:36am UTC](https://discourse.julialang.org/t/lotka-volterra-neural-ode/133159 "2025-10-19T09:36:47Z")

</div>

Hello All, Just started learning about neural ODEs, i was trying to solve the Lotka Volterra equation using neural ODE. here is my code using JLD, Lux, DiffEqFlux, DifferentialEquations, Optimization, OptimizationOpt…

---

## [Trying to run the Transformers'.jl copy task demo - errors](https://discourse.julialang.org/t/trying-to-run-the-transformers-jl-copy-task-demo-errors/133208)

<div class="topic-metadata">

**Author:** [@roeya](https://discourse.julialang.org/u/roeya)\
**Replies:** 0\
**Last updated:** [October 16, 2025, 2:36pm UTC](https://discourse.julialang.org/t/trying-to-run-the-transformers-jl-copy-task-demo-errors/133208 "2025-10-16T14:36:48Z")

</div>

Does this package is still supported? I see it is not compatible with new Flux.jl 0.16.X and the copy task in the documentation is not working as it is written someone can help with this?

---

## [Julia implementation of Liquid Neural Networks - anyone wanna help make one?](https://discourse.julialang.org/t/julia-implementation-of-liquid-neural-networks-anyone-wanna-help-make-one/100953)

<div class="topic-metadata">

**Author:** [@afishy](https://discourse.julialang.org/u/afishy)\
**Replies:** 6\
**Last updated:** [October 14, 2025, 11:38pm UTC](https://discourse.julialang.org/t/julia-implementation-of-liquid-neural-networks-anyone-wanna-help-make-one/100953 "2025-10-14T23:38:59Z")

</div>

Following a thread on machine-learning on Julia slack, i’m interested in putting together a Julia implementation of “Liquid Neural Networks”. These are time-adaptive neural networks, inspired by neuroscience models, wher…

---

## [Help understanding non-mutating function in Lux.Training](https://discourse.julialang.org/t/help-understanding-non-mutating-function-in-lux-training/133137)

<div class="topic-metadata">

**Author:** [@IBArbitrary](https://discourse.julialang.org/u/IBArbitrary)\
**Replies:** 1\
**Last updated:** [October 14, 2025, 6:36pm UTC](https://discourse.julialang.org/t/help-understanding-non-mutating-function-in-lux-training/133137 "2025-10-14T18:36:49Z")

</div>

The Training.apply\_gradient non-mutating function is implemented as below in Lux.jl: function apply\_gradients(ts::TrainState, grads) optimizer\_state, ps = Optimisers.update(ts.optimizer\_state, ts.parameters, grads) …

[Previous page](https://discourse.julialang.org/c/domain/ml/24.md)

[Next page](https://discourse.julialang.org/c/domain/ml/24.md?page=2)