Post
57
I built a small Neural Physics Engine from scratch
The idea I wanted to test: in a projective-dynamics solver, could you replace each hand-derived local constraint projection with a learned one, while keeping the analytic parts (rotations, the global solve) exactly as they are? It's one tiny network, shared across every element and across constraint types through material tokens. A new material isn't a new network, just a new token row. Fluids fall out of the same idea, with water treated as one more token.
A few things held up in testing: one tied projector matched five separate per-material solutions, the neural fluid tracked the exact analytic solver closely on a dam-break sim, and a learned warm-start trimmed solver iterations without touching correctness.
Try it here:
Dam Break Demo:
https://quazim0t0-neural-physics-engine-demo.hf.space/
FPS Shooter Demo:
https://quazim0t0-neural-combat-evolved.hf.space/
Model Repo:
Quazim0t0/neural-physics-engine
The idea I wanted to test: in a projective-dynamics solver, could you replace each hand-derived local constraint projection with a learned one, while keeping the analytic parts (rotations, the global solve) exactly as they are? It's one tiny network, shared across every element and across constraint types through material tokens. A new material isn't a new network, just a new token row. Fluids fall out of the same idea, with water treated as one more token.
A few things held up in testing: one tied projector matched five separate per-material solutions, the neural fluid tracked the exact analytic solver closely on a dam-break sim, and a learned warm-start trimmed solver iterations without touching correctness.
Try it here:
Dam Break Demo:
https://quazim0t0-neural-physics-engine-demo.hf.space/
FPS Shooter Demo:
https://quazim0t0-neural-combat-evolved.hf.space/
Model Repo:
Quazim0t0/neural-physics-engine