most citedLearning Articulated Rigid Body Dynamics with Lagrangian Graph Neural Network

16 citations · 29 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG2023

CoDBench: A Critical Evaluation of Data-driven Models for Continuous Dynamical Systems

Priyanshu Burark, Karn Tiwari, Meer Mehran Rashid +2

Continuous dynamical systems, characterized by differential equations, are ubiquitously used to model several important problems: plasma dynamics, flow through porous media, weathe…

cs.CL20233 cited

MaScQA: A Question Answering Dataset for Investigating Materials Science Knowledge of Large Language Models

Mohd Zaki, Jayadeva, Mausam +1

Information extraction and textual comprehension from materials literature are vital for developing an exhaustive knowledge base that enables accelerated materials discovery. Langu…

cond-mat.mtrl-sci20232 cited

Revealing the Predictive Power of Neural Operators for Strain Evolution in Digital Composites

Meer Mehran Rashid, Souvik Chakraborty, N. M. Anoop Krishnan

The demand for high-performance materials, along with advanced synthesis technologies such as additive manufacturing and 3D printing, has spurred the development of hierarchical co…

cond-mat.mtrl-sci20232 cited

Glass Hardness: Predicting Composition and Load Effects via Symbolic Reasoning-Informed Machine Learning

Sajid Mannan, Mohd Zaki, Suresh Bishnoi +8

Glass hardness varies in a non-linear fashion with the chemical composition and applied load, a phenomenon known as the indentation size effect (ISE), which is challenging to predi…

cs.CV2022

Cementron: Machine Learning the Constituent Phases in Cement Clinker from Optical Images

Mohd Zaki, Siddhant Sharma, Sunil Kumar Gurjar +3

Cement is the most used construction material. The performance of cement hydrate depends on the constituent phases, viz. alite, belite, aluminate, and ferrites present in the cemen…

cs.LG20221 cited

Learning the Dynamics of Particle-based Systems with Lagrangian Graph Neural Networks

Ravinder Bhattoo, Sayan Ranu, N. M. Anoop Krishnan

Physical systems are commonly represented as a combination of particles, the individual dynamics of which govern the system dynamics. However, traditional approaches require the kn…