PyCM
PyCM: Multiclass confusion matrix library in Python - Published in JOSS (2018)
DeepRiver
DeepRiver: A Deep Learning Library for Data Streams - Published in JOSS (2025)
FastVPINNs
FastVPINNs: An efficient tensor-based Python library for solving partial differential equations using hp-Variational Physics Informed Neural Networks - Published in JOSS (2024)
DeepReg
DeepReg: a deep learning toolkit for medical image registration - Published in JOSS (2020)
ivis
ivis: dimensionality reduction in very large datasets using Siamese Networks - Published in JOSS (2019)
ECabc
ECabc: A feature tuning program focused on Artificial Neural Network hyperparameters - Published in JOSS (2019)
BlueCelluLab
BlueCelluLab: Biologically Detailed Neural Network Experimentation API - Published in JOSS (2024)
ATHENA
ATHENA: A Fortran package for neural networks - Published in JOSS (2024)
VisualTorch
VisualTorch: Streamlining Visualization for PyTorch Neural Network Architectures - Published in JOSS (2024)
GraphNeT
GraphNeT: Graph neural networks for neutrino telescope event reconstruction - Published in JOSS (2023)
`hessQuik`
`hessQuik`: Fast Hessian computation of composite functions - Published in JOSS (2022)
nap
nap: A molecular dynamics package with parameter-optimization programs for classical and machine-learning potentials - Published in JOSS (2021)
lattice-symmetries
lattice-symmetries: A package for working with quantum many-body bases - Published in JOSS (2021)
Text detection in screen images with a Convolutional Neural Network
Text detection in screen images with a Convolutional Neural Network - Published in JOSS (2017)
tensorcircuit
Tensor network based quantum software framework for the NISQ era
DEEPaaS API
DEEPaaS API: a REST API for Machine Learning and Deep Learning models - Published in JOSS (2019)
tensorcircuit-ng
The next-gen tensor network based quantum software framework: superseding the original TensorCircuit
deepxde
A library for scientific machine learning and physics-informed learning
analogvnn
A fully modular framework for modeling and optimizing analog neural networks
reflame
reflame: Revolutionizing Functional Link Neural Network by Metaheuristic Optimization
ncnn
ncnn is a high-performance neural network inference framework optimized for the mobile platform
NeuralPDE
Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
pytorch-ignite
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
uform
Pocket-Sized Multimodal AI for content understanding and generation across multilingual texts, images, and 🔜 video, up to 5x faster than OpenAI CLIP and LLaVA 🖼️ & 🖋️
vehicle-lang
A toolkit for enforcing logical specifications on neural networks
orthoseg
OrthoSeg makes it easy to train neural networks to segment orthophotos.
sai
Using explainable to identify regional climate signals to stratospheric aerosol injection
https://github.com/materialsvirtuallab/m3gnet
Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.
ClosedLoopReachability
Reachability analysis for closed-loop control systems in Julia
goneat
The GOLang implementation of NeuroEvolution of Augmented Topologies (NEAT) method to evolve and train Artificial Neural Networks without error back propagation
transformers-interpret
Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.
pennylane
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Built by researchers, for research.
NN-SVG
NN-SVG: Publication-Ready Neural Network Architecture Schematics - Published in JOSS (2019)
burn
Burn is a next generation Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.
mxnet.sharp
.NET Standard bindings for Apache MxNet with Imperative, Symbolic and Gluon Interface for developing, training and deploying Machine Learning models in C#. https://mxnet.tech-quantum.com/
https://github.com/ourownstory/neural_prophet
NeuralProphet: A simple forecasting package
https://github.com/nixtla/neuralforecast
Scalable and user friendly neural :brain: forecasting algorithms.
chemprop
Fast and scalable uncertainty quantification for neural molecular property prediction, accelerated optimization, and guided virtual screening.
mljar-supervised
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
ECNet
ECNet: Large scale machine learning projects for fuel property prediction - Published in JOSS (2017)
shiba-model
Pytorch implementation and pre-trained Japanese model for CANINE, the efficient character-level transformer.
deepfastmlu
Machine learning utilities to help speed up the prototyping process.
matchzoo
Facilitating the design, comparison and sharing of deep text matching models.
predictgmstrate
Using a neural network to predict changes in the rate of global mean surface temperature warming
nerlnet
Nerlnet is a framework for research and development of distributed machine learning models on IoT
evidential-deep-learning
Learn fast, scalable, and calibrated measures of uncertainty using neural networks!
bluecloud-plankton
Spatial interpolation of plankton data using a neural network
scimlbenchmarksoutput
SciML-Bench Benchmarks for Scientific Machine Learning (SciML), Physics-Informed Machine Learning (PIML), and Scientific AI Performance
https://github.com/cog-imperial/omlt
Represent trained machine learning models as Pyomo optimization formulations
ebtorch
🤓🔥 Collection of PyTorch additions, extensions, utilities, uses and abuses
https://github.com/tensorflow/tfjs
A WebGL accelerated JavaScript library for training and deploying ML models.
https://github.com/csinva/interpretable-embeddings
Interpretable text embeddings by asking LLMs yes/no questions (NeurIPS 2024)
pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
hierarchical-dnn-interpretations
Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
seglight
Super fast and real-time semantic segmentation (cpu only) can be use for 1 core cpu
netron
Visualizer for neural network, deep learning and machine learning models
torchdyn
A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods
https://github.com/awslabs/multi-model-server
Multi Model Server is a tool for serving neural net models for inference
computer-vision-in-action
A computer vision closed-loop learning platform where code can be run interactively online. 学习闭环《计算机视觉实战演练:算法与应用》中文电子书、源码、读者交流社区(持续更新中 ...) 📘 在线电子书 https://charmve.github.io/computer-vision-in-action/ 👇项目主页
https://github.com/ctftamu/sl-gps
Repository to create neural network architecture for dynamic chemistry reduction based on Global Pathway Selection
https://github.com/hongbo-miao/hongbomiao.com
A personal research and development (R&D) lab that facilitates the sharing of knowledge.
https://github.com/epsilla-cloud/vectordb
Epsilla is a high performance Vector Database Management System
geoconv
A Python library for end-to-end learning on surfaces. It implements pre-processing functions that include geodesic algorithms, neural network layers that operate on surfaces, visualization tools and benchmarking functionalities.
sinfnet
A collection of datasets and neural networks for microorganism image classification
itclust
Iterative transfer learning with neural network improves clustering and cell type classification in single-cell RNA-seq analysis
deep-smoke-machine
Deep learning models and dataset for recognizing industrial smoke emissions
https://github.com/bencevans/camtrap-detector
Detect Animals, Humans and Vehicles in Camera Trap Imagery. Powered by MegaDetector v5.
bimp
Code to reproduce the experiments of ICLR2023-paper: How I Learned to Stop Worrying and Love Retraining
https://github.com/longxingtan/time-series-prediction
tfts: Time Series Deep Learning Models in TensorFlow
https://github.com/csinva/gan-vae-pretrained-pytorch
Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.
mocapnet
We present MocapNET, a real-time method that estimates the 3D human pose directly in the popular Bio Vision Hierarchy (BVH) format, given estimations of the 2D body joints originating from monocular color images. Our contributions include: (a) A novel and compact 2D pose NSRM representation. (b) A human body orientation classifier and an ensemble of orientation-tuned neural networks that regress the 3D human pose by also allowing for the decomposition of the body to an upper and lower kinematic hierarchy. This permits the recovery of the human pose even in the case of significant occlusions. (c) An efficient Inverse Kinematics solver that refines the neural-network-based solution providing 3D human pose estimations that are consistent with the limb sizes of a target person (if known). All the above yield a 33% accuracy improvement on the Human 3.6 Million (H3.6M) dataset compared to the baseline method (MocapNET) while maintaining real-time performance
t81_558_deep_learning
T81-558: Keras - Applications of Deep Neural Networks @Washington University in St. Louis
https://github.com/csinva/matching-with-gans
Matching in GAN latent space for better bias benchmarking and semantic image editing. 👶🏻🧒🏾👩🏼🦰👱🏽♂️👴🏾
quickai
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
https://github.com/awslabs/renate
Library for automatic retraining and continual learning
aifororcas-livesystem
Real-time AI-assisted killer whale notification system (model and moderator portal) :star: