Top 18 Sde Open-Source Projects

• stable-baselines3

  46 8,032 8.2 Python

  PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

  

Project mention: Sim-to-real RL pipeline for open-source wheeled bipeds | /r/robotics | 2023-12-09

The latest release (v3.0.0) of Upkie's software brings a functional sim-to-real reinforcement learning pipeline based on Stable Baselines3, with standard sim-to-real tricks. The pipeline trains on the Gymnasium environments distributed in upkie.envs (setup: pip install upkie) and is implemented in the PPO balancer. Here is a policy running on an Upkie:

• moreThanFAANGM

  10 4,356 6.9

  This repository contains opportunities for you to apply to more than 400 product base companies(NOT JUST FAANGM) & good start-ups.

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• DifferentialEquations.jl

  6 2,769 7.2 Julia

  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.

  

• rl-baselines3-zoo

  11 1,796 6.2 Python

  A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

  

Project mention: Can't solve MountainCar-v0 with A2C algorithm (stable-baselines3) | /r/reinforcementlearning | 2023-06-27

I'm trying to solve MountainCar-v0 enviroment from gymnasium with the A2C algorithm and the agent doesn't find a solution. I checked this so I added import stable_baselines3.common.sb2_compat.rmsprop_tf_like as RMSpropTFLike. Also checked the rl-baselines3-zoo for the hyperparameter tuning. So my code is:

• ModelingToolkit.jl

  15 1,363 9.8 Julia

  An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations

  

• SciMLTutorials.jl

  1 709 1.5 CSS

  Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.

  

• diffeqpy

  4 498 7.7 Python

  Solving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organization

  

• SaaSHub

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• stable-baselines3-contrib

  6 429 6.7 Python

  Contrib package for Stable-Baselines3 - Experimental reinforcement learning (RL) code

  

Project mention: Problem with Truncated Quantile Critics (TQC) and n-step learning algorithm. | /r/reinforcementlearning | 2023-12-09

# https://github.com/Stable-Baselines-Team/stable-baselines3-contrib/blob/master/sb3_contrib/tqc/tqc.py :

• Catalyst.jl

  2 422 9.5 Julia

  Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.

  

• SciMLSensitivity.jl

  2 316 9.5 Julia

  A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.

  

• DiffEqBase.jl

  1 298 9.3 Julia

  The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems

  

• SciMLBenchmarks.jl

  10 294 9.7 MATLAB

  Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R

  

• DiffEqGPU.jl

  2 267 8.1 Julia

  GPU-acceleration routines for DifferentialEquations.jl and the broader SciML scientific machine learning ecosystem

  

Project mention: 2023 was the year that GPUs stood still | news.ycombinator.com | 2023-12-29

Indeed, and this year we created a system for compiling ODE code not just optimized CUDA kernels but also OneAPI kernels, AMD GPU kernels, and Metal. Peer reviewed version is here (https://www.sciencedirect.com/science/article/abs/pii/S00457...), open access is here (https://arxiv.org/abs/2304.06835), and the open source code is at https://github.com/SciML/DiffEqGPU.jl. The key that the paper describes is that in this case kernel generation is about 20x-100x faster than PyTorch and Jax (see the Jax compilation in multiple ways in this notebook https://colab.research.google.com/drive/1d7G-O5JX31lHbg7jTzz..., extra overhead though from calling Julia from Python but still shows a 10x).

The point really is that while deep learning libraries are amazing, at the end of the day they are DSL and really pull towards one specific way of computing and parallelization. It turns out that way of parallelizing is good for deep learning, but not for all things you may want to accelerate. Sometimes (i.e. cases that aren't dominated by large linear algebra) building problem-specific kernels is a major win, and it's over-extrapolating to see ML frameworks do well with GPUs and think that's the only thing that's required. There are many ways to parallelize a code, ML libraries hardcode a very specific way, and it's good for what they are used for but not every problem that can arise.

• StochasticDiffEq.jl

  1 235 7.8 Julia

  Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem

  

• ModelingToolkitStandardLibrary.jl

  2 99 9.1 Julia

  A standard library of components to model the world and beyond

  

• Design-Patterns-And-Principles

  1 97 0.0 Kotlin

  A collection of a number of design patterns and principles written in Kotlin

• PyDaddy

  1 88 7.5 Python

  Python package to discover stochastic differential equations from time series data

  

• DiffEqDevTools.jl

  3 46 8.5 Julia

  Benchmarking, testing, and development tools for differential equations and scientific machine learning (SciML)

  

• SaaSHub

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• A note from our sponsor - SaaSHub
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