Stars
A Large-Scale Multimodal Car Dataset with Computational Fluid Dynamics Simulations and Deep Learning Benchmarks
A JAX-based research framework for differentiable and parallelizable acoustic simulations, on CPU, GPUs and TPUs
Data-driven reduced order modeling for nonlinear dynamical systems
Data-driven reduced order modeling for nonlinear dynamical systems
Generalized sparse regression for continuous and discrete data
Apply hard physical constraints directly to Reservoir Computers!
differentiable (magneto)hydrodynamics for astrophysics in JAX, 📖 https://jf1uids.web.app/
A multi-agent reinforcement learning environment to design and benchmark control strategies aimed at reducing drag in turbulent open channel flow
XLB: Accelerated Lattice Boltzmann (XLB) for Physics-based ML
A generative world for general-purpose robotics & embodied AI learning.
[ICLR 2023] FluidLab: A Differentiable Environment for Benchmarking Complex Fluid Manipulation
Incompressible Navier-Stokes solver
A library for programmatically generating equivariant layers through constraint solving
NeuralFoil is a practical airfoil aerodynamics analysis tool using physics-informed machine learning, in pure Python/NumPy.
Benchmarking RL generalization in an interpretable way.
Aircraft design optimization made fast through computational graph transformations (e.g., automatic differentiation). Composable analysis tools for aerodynamics, propulsion, structures, trajectory …
Python toolbox for optimization on Riemannian manifolds with support for automatic differentiation
Computations and statistics on manifolds with geometric structures.
Large-Scale Multimodal Dataset of Astronomical Data
A 15TB Collection of Physics Simulation Datasets
Controlgym: Large-Scale Control Environments for Benchmarking Reinforcement Learning Algorithms
imgeorgiev / DiffRL
Forked from NVlabs/DiffRLLearning Optimal Policies Through Contact in Differentiable Simulation