63 citations · 77 across the 17 of their papers we have counts for
17 papers
Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning
Olabode T. Ajenifujah, Amir Barati Farimani
Additive manufacturing (AM) is a rapidly evolving technology that has attracted applications across a wide range of fields due to its ability to fabricate complex geometries. Howev…
Zero-Shot Uncertainty Quantification using Diffusion Probabilistic Models
Dule Shu, Amir Barati Farimani
The success of diffusion probabilistic models in generative tasks, such as text-to-image generation, has motivated the exploration of their application to regression problems commo…
Multi-Peptide: Multimodality Leveraged Language-Graph Learning of Peptide Properties
Srivathsan Badrinarayanan, Chakradhar Guntuboina, Parisa Mollaei +1
Peptides are essential in biological processes and therapeutics. In this study, we introduce Multi-Peptide, an innovative approach that combines transformer-based language models w…
GradNav: Accelerated Exploration of Potential Energy Surfaces with Gradient-Based Navigation
Janghoon Ock, Parisa Mollaei, Amir Barati Farimani
The exploration of molecular systems' potential energy surface is important for comprehending their complex behaviors, particularly through identifying various metastable states. H…
AlloyBERT: Alloy Property Prediction with Large Language Models
Akshat Chaudhari, Chakradhar Guntuboina, Hongshuo Huang +1
The pursuit of novel alloys tailored to specific requirements poses significant challenges for researchers in the field. This underscores the importance of developing predictive te…
SculptDiff: Learning Robotic Clay Sculpting from Humans with Goal Conditioned Diffusion Policy
Alison Bartsch, Arvind Car, Charlotte Avra +1
Manipulating deformable objects remains a challenge within robotics due to the difficulties of state estimation, long-horizon planning, and predicting how the object will deform gi…