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Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
A textbook on parallel computing and scientific machine learning methods and applications
Official code for a fast ODE solver for diffusion probabilistic model sampling in 10 steps
A Julia framework for acausal modeling, symbolic math, and parallelized scientific machine learning.
A collection of resources for working with differential equations, deep learning, and dynamical systems.
Physics-Informed Neural Networks (PINN) Solvers for accelerated simulation and scientific machine learning.
MixGRPO is a Python library that unlocks flow-based GRPO efficiency with mixed ODE-SDE for diffusion and reinforcement learning.
A Python library for building continuous-time neural networks and neural ODEs.
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