Taichi
DiffTaichi: Differentiable Programming for Physical Simulation
Differentiable programming in Taichi allows you to optimize neural network controllers efficiently with brute-force gradient descent, instead of using reinforcement learning. It is much more efficient than REINFORCE update. The DiffTaichi differentiable programming framework is now officially part of Taichi.
Official Materials
Related Projects
- ICLR 2023: PAC-NeRF: Physics Augmented Continuum Neural Radiance Fields for Geometry-Agnostic System Identification
- ICLR 2022: DiffSkill: Skill Abstraction from Differentiable Physics for Deformable Object Manipulations with Tools
- ICLR 2021: PlasticineLab: A Soft-Body Manipulation Benchmark with Differentiable Physics
- NeuIPS 2019: Differentiable cloth simulation for inverse problems