More to correct directory

docs/make.jl

@@ -88,7 +88,7 @@ makedocs(; sitename="Lux.jl Documentation",
         repo="github.com/LuxDL/Lux.jl", devbranch="main", devurl="dev",
         deploy_url="https://lux.csail.mit.edu", deploy_decision),
     draft=false,
-    pages=pages)
+    pages)
 
 deploydocs(; repo="github.com/LuxDL/Lux.jl.git",
     push_preview=true, target="build", devbranch="main")

docs/src/.vitepress/config.mts

@@ -137,6 +137,25 @@ export default defineConfig({
                     {
                         text: 'Advanced', collapsed: false, items: [
                             { text: 'Training a Neural ODE to Model Gravitational Waveforms', link: '/tutorials/advanced/1_GravitationalWaveForm' }]
+                    },
+                    {
+                        text: '3rd Party Tutorials', collapsed: true, items: [
+                            {
+                                text: 'PINNs (NeuralPDE.jl)', link: 'https://docs.sciml.ai/NeuralPDE/stable/tutorials/pdesystem/'
+                            },
+                            {
+                                text: 'UDEs (SciMLSensitivity.jl)', link: 'https://docs.sciml.ai/SciMLSensitivity/stable/tutorials/data_parallel/'
+                            },
+                            {
+                                text: 'Neural DEs (DiffEqFlux.jl)', link: 'https://docs.sciml.ai/DiffEqFlux/stable/examples/neural_ode/'
+                            },
+                            {
+                                text: 'DEQs (DeepEquilibriumNetworks.jl)', link: 'https://docs.sciml.ai/DeepEquilibriumNetworks/stable/tutorials/basic_mnist_deq/'
+                            },
+                            {
+                                text: 'Medical Image Segmentation', link: 'https://github.com/Dale-Black/ComputerVisionTutorials.jl/'
+                            }
+                        ]
                     }]
             },
             "/manual/": {

docs/src/tutorials/index.md

@@ -5,34 +5,34 @@ import Gallery from "../components/Gallery.vue";
 const beginner = [
   {
     href: "beginner/1_Basics",
-    src: "../assets/tutorials/julia.jpg",
+    src: "https://picsum.photos/350/250?image=444",
     caption: "Julia & Lux for the Uninitiated",
     desc: "How to get started with Julia and Lux for those who have never used Julia before."
   },
   {
     href: "beginner/2_PolynomialFitting",
-    src: "../assets/tutorials/mlp.webp",
+    src: "../mlp.webp",
     caption: "Fitting a Polynomial using MLP",
     desc: "Learn the Basics of Lux by fitting a Multi-Layer Perceptron to a Polynomial."
   },
   {
     href: "beginner/3_SimpleRNN",
-    src: "../assets/tutorials/lstm-illustrative.webp",
+    src: "../lstm-illustrative.webp",
     caption: "Training a Simple LSTM",
     desc: "Learn how to define custom layers and train an RNN on time-series data."
   },
   {
     href: "beginner/4_SimpleChains",
-    src: "../assets/tutorials/blas_optimizations.jpg",
+    src: "../blas_optimizations.jpg",
     caption: "Use SimpleChains.jl as a Backend",
-    desc: "Learn how to train small neural networks really fast"
+    desc: "Learn how to train small neural networks really fast on CPU."
   }
 ];
 
 const intermediate = [
   {
     href: "intermediate/1_NeuralODE",
-    src: "../assets/tutorials/mnist.jpg",
+    src: "../mnist.jpg",
     caption: "MNIST Classification using Neural ODE",
     desc: "Train a Neural Ordinary Differential Equations to classify MNIST Images."
   },
@@ -44,7 +44,7 @@ const intermediate = [
   },
   {
     href: "intermediate/3_HyperNet",
-    src: "../assets/tutorials/hypernet.jpg",
+    src: "../hypernet.jpg",
     caption: "Training a HyperNetwork",
     desc: "Train a hypernetwork to work on multiple datasets by predicting neural network parameters."
   }
@@ -53,14 +53,37 @@ const intermediate = [
 const advanced = [
   {
     href: "advanced/1_GravitationalWaveForm",
-    src: "../assets/tutorials/gravitational_waveform.png",
+    src: "../gravitational_waveform.png",
     caption: "Neural ODE to Model Gravitational Waveforms",
     desc: "Training a Neural ODE to fit simulated data of gravitational waveforms."
   }
 ];
 
-const aggregated = [
-
+const thrid_party = [
+  {
+    href: "https://docs.sciml.ai/Overview/stable/showcase/pinngpu/",
+    src: "../pinn.gif",
+    caption: "GPU-Accelerated Physics-Informed Neural Networks",
+    desc: "Use Machine Learning (PINNs) to solve the Heat Equation PDE on a GPU."
+  },
+  {
+    href: "https://docs.sciml.ai/DiffEqFlux/stable/examples/neural_ode_weather_forecast/",
+    src: "../weather-neural-ode.gif",
+    caption: "Weather Forecasting with Neural ODEs",
+    desc: "Train a neural ODEs to a multidimensional weather dataset and use it for weather forecasting."
+  },
+  {
+    href: "https://docs.sciml.ai/SciMLSensitivity/stable/examples/sde/SDE_control/",
+    src: "../neural-sde.png",
+    caption: "Controlling Stochastic Differential Equations",
+    desc: "Control the time evolution of a continuously monitored qubit described by an SDE with multiplicative scalar noise."
+  },
+  {
+    href: "https://github.com/Dale-Black/ComputerVisionTutorials.jl/",
+    src: "https://raw.githubusercontent.com/Dale-Black/ComputerVisionTutorials.jl/main/assets/image-seg-green.jpeg",
+    caption: "Medical Image Segmentation",
+    desc: "Explore various aspects of deep learning for medical imaging and a comprehensive overview of Julia packages."
+  }
 ];
 </script>
 
@@ -78,7 +101,7 @@ const aggregated = [
 
 <Gallery :images="advanced" />
 
-## Aggregated Tutorials
+## Selected 3rd Party Tutorials
 
 ::: warning
 
@@ -91,5 +114,13 @@ of them are non-functional and we will try to get them updated.
 
 :::
 
-<Gallery :images="aggregated" />
+<Gallery :images="thrid_party" />
+
+
+::: tip
+
+If you found an amazing tutorial showcasing `Lux.jl` online, or wrote one yourself, please
+open an issue or PR to add it to the list!
+
+:::
 ```