205 citations · 429 across the 4 of their papers we have counts for
4 papers
Algebraic Language Models for Inverse Design of Metamaterials via Diffusion Transformers
Li Zheng, Siddhant Kumar, Dennis M. Kochmann
Generative machine learning models have revolutionized material discovery by capturing complex structure-property relationships, yet extending these approaches to the inverse desig…
HyperCAN: Hypernetwork-Driven Deep Parameterized Constitutive Models for Metamaterials
Li Zheng, Dennis M. Kochmann, Siddhant Kumar
We introduce HyperCAN, a machine learning framework that utilizes hypernetworks to construct adaptable constitutive artificial neural networks for a wide range of beam-based metama…
Unifying the design space and optimizing linear and nonlinear truss metamaterials by generative modeling
Li Zheng, Konstantinos Karapiperis, Siddhant Kumar +1
The rise of machine learning has fueled the discovery of new materials and, especially, metamaterials--truss lattices being their most prominent class. While their tailorable prope…
Data-driven topology optimization of spinodoid metamaterials with seamlessly tunable anisotropy
Li Zheng, Siddhant Kumar, Dennis M. Kochmann
We present a two-scale topology optimization framework for the design of macroscopic bodies with an optimized elastic response, which is achieved by means of a spatially-variant ce…