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17 search results found

Flux.jl ⭐ 4,318

Relax! Flux is the ML library that doesn't make you tensor

Knet.jl ⭐ 1,336

Koç University deep learning framework.

Beautifulalgorithms.jl ⭐ 1,281

Concise and beautiful algorithms written in Julia

Neuralpde.jl ⭐ 864

Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation

Diffeqflux.jl ⭐ 810

Universal neural differential equations with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods

Explicitly Parameterized Neural Networks in Julia

Componentarrays.jl ⭐ 258

Arrays with arbitrarily nested named components.

Deepneuralclassifier ⭐ 243

Deep neural network using rectified linear units to classify hand written symbols from the MNIST dataset.

Neuralverification.jl ⭐ 215

Methods to soundly verify deep neural networks

Autograd.jl ⭐ 160

Julia port of the Python autograd package.

Adcme.jl ⭐ 158

Automatic Differentiation Library for Computational and Mathematical Engineering

Merlin.jl ⭐ 138

Deep Learning for Julia

Invertiblenetworks.jl ⭐ 131

A Julia framework for invertible neural networks

Mipverify.jl ⭐ 111

Evaluating Robustness of Neural Networks with Mixed Integer Programming

Recurrentnn.jl ⭐ 96

Deep RNN, LSTM, GRU, GF-RNN, and GF-LSTMs in Julia

Juliaconnector ⭐ 93

A functionally oriented interface for calling Julia from R

Betaml.jl ⭐ 83

Beta Machine Learning Toolkit

Open-source, graph-based Python code generator and analysis toolbox for dynamical systems (pre-implemented and custom models). Most pre-implemented models belong to the family of neural population models.

Highdimpde.jl ⭐ 61

A Julia package for Deep Backwards Stochastic Differential Equation (Deep BSDE) and Feynman-Kac methods to solve high-dimensional PDEs without the curse of dimensionality

Julia artificial neural networks

Latte.jl ⭐ 53

A high-performance DSL for deep neural networks in Julia

Knet The Julia Dope ⭐ 52

An interactive book on deep learning. Much easy, so Knet. Wow.

Deepequilibriumnetworks.jl ⭐ 46

Implicit Layer Machine Learning via Deep Equilibrium Networks, O(1) backpropagation with accelerated convergence.

Backpropneuralnet.jl ⭐ 45

A neural network in Julia

Keras.jl ⭐ 42

A julia wrapper for https://keras.io

Closedloopreachability.jl ⭐ 42

Reachability analysis for closed-loop control systems

Naivegaflux.jl ⭐ 41

Evolve Flux networks from scratch!

Restrictedboltzmannmachine ⭐ 35

Neural network trained as a generative model on the MNIST dataset using Persistent Contrastive Divergence.

Transformations.jl ⭐ 31

Static transforms, activation functions, and other implementations of LearnBase abstractions

Protograd.jl ⭐ 31

Deep learning 99% fat free

Boltzmannmachines.jl ⭐ 28

A Julia package for training and evaluating multimodal deep Boltzmann machines

Hydra.jl ⭐ 27

SPMD + Neural Nets

Gigasom.jl ⭐ 26

Huge-scale, high-performance flow cytometry clustering in Julia

Regneuralde.jl ⭐ 25

Official Implementation of "Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver Heuristics" (ICML 2021)

Mlplots.jl ⭐ 24

Plotting recipes for statistics and machine learning using Plots.jl

Naivenasflux.jl ⭐ 23

Your local Flux surgeon

Textmodels.jl ⭐ 23

Neural Network based models for Natural Language Processing

Neuralquantum.jl ⭐ 20

Neural-Network representation of Quantum Systems

Naivenaslib.jl ⭐ 17

Relentless mutation!!

Keras.jl ⭐ 14

Run keras models with a Flux backend

Scimlbenchmarksoutput ⭐ 13

SciML-Bench Benchmarks for Scientific Machine Learning (SciML), Physics-Informed Machine Learning (PIML), and Scientific AI Performance

Compositionalnetworks.jl ⭐ 13

A Julia package for Interpretable Compositional Networks (ICN), a variant of neural networks, allowing the user to get interpretable results, unlike regular artificial neural networks.

Adversarialprediction.jl ⭐ 12

Easily optimize generic performance metrics in differentiable learning.

Nnfem.jl ⭐ 12

Neural Network Approach for Data-Driven Constitutive Modeling

Implementation of Wasserstein GAN using Knet

Segmentation.jl ⭐ 12

Segmentation models in Julia

Am205_final ⭐ 11

Solving ODE by artificial neural networks

Control_neuralode ⭐ 9

On the use of NeuralODEs as optimal control policies: I.O. Sandoval, P. Petsagkourakis, E. A. del Rio-Chanona, “Neural ODEs as Feedback Policies for Nonlinear Optimal Control” The 22nd World Congress of the International Federation of Automatic Control (IFAC 2023)

Scatternnlib.jl ⭐ 9

A scatter operation library for neural network

Monodepth2.jl ⭐ 9

Self-supervised monocular depth estimation

Horizontalcas ⭐ 9

Efficientnet.jl ⭐ 8

EfficientNet implementation in Julia

Pydatabratislava ⭐ 8

All the documents for PyDataBratislava

Knetnlpmodels.jl ⭐ 8

An NLPModels Interface to Knet

Adversarial.jl ⭐ 7

Adversarial attacks for Neural Networks written with FluxML

Julia_notebooks ⭐ 7

Jupyter notebooks on Julia programming

Gradvalley.jl ⭐ 6

A new lightweight package for Deep Learning with Julia

Binarycommitteemachinefbp.jl ⭐ 5

Focusing Belief Propagation on Commitee machines with binary weights

Simplenn.jl ⭐ 5

Simple and fast neural network in Julia from scratch

Nervoso.jl ⭐ 5

Simple Neural Networks library written in Julia

Neuralnetwork.jl ⭐ 5

Implementation of neural network from Andrew Ng as from Coursera

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