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20222026
most citedMOLPIPx: an end-to-end differentiable package for permutationally invariant polynomials in Python and Rust

3 citations · 5 across the 4 of their papers we have counts for

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physics.chem-ph2024★ 3 cited

MOLPIPx: an end-to-end differentiable package for permutationally invariant polynomials in Python and Rust

Manuel S. Drehwald, Asma Jamali, Rodrigo A. Vargas-Hernández

In this work, we present MOLPIPx, a versatile library designed to seamlessly integrate Permutationally Invariant Polynomials (PIPs) with modern machine learning frameworks, enablin…

cs.CV2024

Learning Zero-Shot Material States Segmentation, by Implanting Natural Image Patterns in Synthetic Data

Sagi Eppel, Jolina Li, Manuel Drehwald +1

Visual recognition of materials and their states is essential for understanding the physical world, from identifying wet regions on surfaces or stains on fabrics to detecting infec…