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Differentiable Material Point Method

A line of robotics and graphics research, beginning with Hu, Liu, Spielberg, Tenenbaum, Freeman, Wu, Rus & Matusik's ChainQueen (ICRA 2019) and continued independently by Bolliger, Fadini, Bambach & Rupenyan (2025), that applies automatic differentiation — reverse-mode AD, whose earliest general, formal statement is Seppo Linnainmaa's 1970 Helsinki master's thesis (published in BIT in 1976) — to the Material Point Method, the numerical scheme Sulsky, Chen/Zhou & Schreyer developed for penetration mechanics starting with SAND-91-7095 (1992). Matters to this vault as the first confirmed genuine mechanism-level bridge between its automatic-differentiation cluster and its Material Point Method cluster — two literatures that originated independently, decades apart, and never cited each other directly; the technique arrived through modern autodiff frameworks (TensorFlow, JAX) rather than through attribution to either founding lineage.

References

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