N. M. Anoop Krishnan

CoRR, 2024

2023

Learning the dynamics of particle-based systems with Lagrangian graph neural networks.

[BibT_eX]

[DOI]

Mach. Learn. Sci. Technol., March, 2023

Reconstructing Materials Tetrahedron: Challenges in Materials Information Extraction.

[BibT_eX]

[DOI]

CoRR, 2023

EGraFFBench: Evaluation of Equivariant Graph Neural Network Force Fields for Atomistic Simulations.

[BibT_eX]

[DOI]

CoRR, 2023

CoNO: Complex Neural Operator for Continuous Dynamical Systems.

[BibT_eX]

[DOI]

Karn Tiwari

Prathosh A P

CoRR, 2023

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

[BibT_eX]

[DOI]

CoRR, 2023

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

[BibT_eX]

[DOI]

CoRR, 2023

Discovering Symbolic Laws Directly from Trajectories with Hamiltonian Graph Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2023

Graph Neural Stochastic Differential Equations for Learning Brownian Dynamics.

[BibT_eX]

[DOI]

CoRR, 2023

StriderNet: A Graph Reinforcement Learning Approach to Optimize Atomic Structures on Rough Energy Landscapes.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Enhancing the Inductive Biases of Graph Neural ODE for Modeling Physical Systems.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

DiSCoMaT: Distantly Supervised Composition Extraction from Tables in Materials Science Articles.

[BibT_eX]

[DOI]

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

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

[BibT_eX]

[DOI]

CoRR, 2022

Predicting Oxide Glass Properties with Low Complexity Neural Network and Physical and Chemical Descriptors.

[BibT_eX]

[DOI]

CoRR, 2022

Learning Rigid Body Dynamics with Lagrangian Graph Neural Network.

[BibT_eX]

[DOI]

CoRR, 2022

Enhancing the Inductive Biases of Graph Neural ODE for Modeling Dynamical Systems.

[BibT_eX]

[DOI]

CoRR, 2022

DiSCoMaT: Distantly Supervised Composition Extraction from Tables in Materials Science Articles.

[BibT_eX]

[DOI]

CoRR, 2022

Unravelling the Performance of Physics-informed Graph Neural Networks for Dynamical Systems.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning Articulated Rigid Body Dynamics with Lagrangian Graph Neural Network.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Looking through glass: Knowledge discovery from materials science literature using natural language processing.

[BibT_eX]

[DOI]

Patterns, 2021

Lagrangian Neural Network with Differentiable Symmetries and Relational Inductive Bias.

[BibT_eX]

[DOI]