N. M. Anoop Krishnan

Orcid: 0000-0003-1500-4947

According to our database1, N. M. Anoop Krishnan authored at least 26 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Discovering symbolic laws directly from trajectories with hamiltonian graph neural networks.
Mach. Learn. Sci. Technol., 2024

CoNO: Complex Neural Operator for Continous Dynamical Physical Systems.
CoRR, 2024

TAGMol: Target-Aware Gradient-guided Molecule Generation.
CoRR, 2024

Are LLMs Ready for Real-World Materials Discovery?
CoRR, 2024

BroGNet: Momentum-Conserving Graph Neural Stochastic Differential Equation for Learning Brownian Dynamics.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Learning the dynamics of particle-based systems with Lagrangian graph neural networks.
Mach. Learn. Sci. Technol., March, 2023

Reconstructing Materials Tetrahedron: Challenges in Materials Information Extraction.
CoRR, 2023

EGraFFBench: Evaluation of Equivariant Graph Neural Network Force Fields for Atomistic Simulations.
CoRR, 2023

CoNO: Complex Neural Operator for Continuous Dynamical Systems.
CoRR, 2023

CoDBench: A Critical Evaluation of Data-driven Models for Continuous Dynamical Systems.
CoRR, 2023

MaScQA: A Question Answering Dataset for Investigating Materials Science Knowledge of Large Language Models.
CoRR, 2023

Graph Neural Stochastic Differential Equations for Learning Brownian Dynamics.
CoRR, 2023

StriderNet: A Graph Reinforcement Learning Approach to Optimize Atomic Structures on Rough Energy Landscapes.
Proceedings of the International Conference on Machine Learning, 2023

Enhancing the Inductive Biases of Graph Neural ODE for Modeling Physical Systems.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

DiSCoMaT: Distantly Supervised Composition Extraction from Tables in Materials Science Articles.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
MatSciBERT.
Dataset, April, 2022

Cementron: Machine Learning the Constituent Phases in Cement Clinker from Optical Images.
CoRR, 2022

Predicting Oxide Glass Properties with Low Complexity Neural Network and Physical and Chemical Descriptors.
CoRR, 2022

Learning Rigid Body Dynamics with Lagrangian Graph Neural Network.
CoRR, 2022

Enhancing the Inductive Biases of Graph Neural ODE for Modeling Dynamical Systems.
CoRR, 2022

DiSCoMaT: Distantly Supervised Composition Extraction from Tables in Materials Science Articles.
CoRR, 2022

Unravelling the Performance of Physics-informed Graph Neural Networks for Dynamical Systems.
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.
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.
Patterns, 2021

Lagrangian Neural Network with Differentiable Symmetries and Relational Inductive Bias.
CoRR, 2021

MatSciBERT: A Materials Domain Language Model for Text Mining and Information Extraction.
CoRR, 2021


  Loading...