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Simulation platform for general-purpose robotics & embodied AI learning.
Burn is a next generation tensor library and Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.
- autodiff
- deep-learning
- machine-learning
- rust
Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learn...
- java
- gpu
- deeplearning
- neural-nets
Open3D: A Modern Library for 3D Data Processing
- mesh-processing
- computer-graphics
- opengl
- cpp
CUDA Templates and Python DSLs for High-Performance Linear Algebra
- cuda
- deep-learning
- deep-learning-library
- cpp
PyTorch3D is FAIR's library of reusable components for deep learning with 3D data
AI Toolkit for Healthcare Imaging
- healthcare-imaging
- deep-learning
- medical-image-computing
- medical-image-processing
Efficiently computes derivatives of NumPy code.
- autograd
- automatic-differentiation
- numpy
- python
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
- drug-discovery
- quantum-chemistry
- deep-learning
- biology
A PyTorch Library for Accelerating 3D Deep Learning Research
- pytorch
- 3d-deep-learning
- neural-networks
- differentiable-rendering
PennyLane is an open-source quantum software platform for quantum computing, quantum machine learning, and quantum chemistry. Create meaningful quantum algorithms, from inspiration to implementation.
Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.
- differential-equations
- differentialequations
- julia
- ode
POT : Python Optimal Transport
- optimal-transport
- numerical-optimization
- machine-learning
- emd
Message Passing Neural Networks for Molecule Property Prediction
- machine-learning
- chemistry
- neural-networks
- drug-discovery
Optax is a gradient processing and optimization library for JAX.
This package contains deep learning models and related scripts for RoseTTAFold
Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
- python
- genetic-algorithm
- optimization
- numpy
Deep probabilistic analysis of single-cell and spatial omics data
- scrna-seq
- variational-bayes
- variational-autoencoder
- cite-seq
Implementation of DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking
- diffusion-models
- docking
- binding
- computational-biology
A research toolkit for particle swarm optimization in Python
- particle-swarm-optimization
- optimization-tools
- pso
- global-optimization
Owl - OCaml Scientific Computing @ https://ocaml.xyz
- matrix
- linear-algebra
- ndarray
- statistical-functions
:chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions
- adaptive-learning
- machine-learning
- python
- live-plots
TorchXRayVision: A library of chest X-ray datasets and models. Classifiers, segmentation, and autoencoders.