If you're interested in AI for materials science (and beyond), come and join this virtual workshop next week (among the long list of great speakers, I will be presenting on our efforts to design architected materials with target mechanical properties on Tuesday).
Check out our new preprint on informing generative diffusion models on sample constraints!
We present a theoretically motivated but easily implementable method to beat SOTA for PDE adherence by almost two orders of magnitude.
https://t.co/4p273MBsQN
Diffusion models are for making fake photos and videos only? How about using video diffusion to not only perdict a cellular structure with a given nonlinear mech. response but also to generate the video showing its stress distribution during a load cycle?
https://t.co/jzlCcncdE8
We have two PhD openings in the Mechanics and Materials Lab at ETH Zurich. Through theory, simulations, and experiments, we will study knotted/woven and straw-based architected materials with new opportunities for controlling nonlinear material behavior:
https://t.co/wX9eiDXOTC
Graph Neural Networks (GNNs) enable faster and more accurate phase space integration compared to classical multivariate quadrature for finite temperature atomistic simulations.
https://t.co/uWTLtNxprt
We have a new PhD vacancy on modeling metallic microstructures with machine learning!
More info/apply here: https://t.co/TetcWR6HHe
Retweets appreciated. :)
@MSETUDELFT@tudelft3mE
Ever wondered how to find a periodic truss with target 3D anisotropic stiffness and density? Try this ML-based inverse design approach: https://t.co/oWdZW8cMR4
Great collaboration with @sidkumar_mech.
#SolidMechanics#MachineLearning