Ravinder Bhattoo
Ravinder Bhattoo
Другие именаRavinder Ravinder, R Ravinder
Postdoctoral Scholar, University of Wisconsin-Madison
Подтвержден адрес электронной почты в домене wisc.edu - Главная страница
Predicting Young's modulus of oxide glasses with sparse datasets using machine learning
S Bishnoi, S Singh, R Ravinder, M Bauchy, NN Gosvami, H Kodamana, ...
Journal of non-crystalline solids 524, 119643, 2019
Deep Learning Aided Rational Design of Oxide Glasses
R Ravinder, KH Sridhara, S Bishnoi, HS Grover, M Bauchy, J Jayadeva, ...
Materials Horizons, 2020
Scalable Gaussian processes for predicting the optical, physical, thermal, and mechanical properties of inorganic glasses with large datasets
S Bishnoi, R Ravinder, HS Grover, H Kodamana, NMA Krishnan
Materials advances 2 (1), 477-487, 2021
Cooling rate effects on the structure of 45S5 bioglass: Insights from experiments and simulations
P Bhaskar, R Kumar, Y Maurya, R Ravinder, AR Allu, S Das, NN Gosvami, ...
Journal of Non-Crystalline Solids 534, 119952, 2020
Artificial intelligence and machine learning in glass science and technology: 21 challenges for the 21st century
R Ravinder, V Venugopal, S Bishnoi, S Singh, M Zaki, HS Grover, ...
International Journal of Applied Glass Science, 2021
Density–stiffness scaling in minerals upon disordering: Irradiation vs. vitrification
NMA Krishnan, R Ravinder, R Kumar, Y Le Pape, G Sant, M Bauchy
Acta Materialia 166, 611-617, 2019
An adaptive, interacting, cluster-based model for predicting the transmission dynamics of COVID-19
R Ravinder, S Singh, S Bishnoi, A Jan, A Sharma, H Kodamana, ...
Heliyon 6 (12), 2020
Glass fracture upon ballistic impact: new insights from peridynamics simulations
J Rivera, J Berjikian, R Ravinder, H Kodamana, S Das, N Bhatnagar, ...
Frontiers in Materials 6, 239, 2019
Evidence of a two-dimensional glass transition in graphene: Insights from molecular simulations
R Ravinder, R Kumar, M Agarwal, NMA Krishnan
Scientific Reports 9 (1), 4517, 2019
Learning articulated rigid body dynamics with lagrangian graph neural network
R Bhattoo, S Ranu, NM Krishnan
Advances in Neural Information Processing Systems 35, 29789-29800, 2022
Interpreting the optical properties of oxide glasses with machine learning and Shapely additive explanations
M Zaki, V Venugopal, R Bhattoo, S Bishnoi, SK Singh, AR Allu, Jayadeva, ...
Journal of the american ceramic society 105 (6), 4046-4057, 2022
Redox sensitive self-assembling dipeptide for sustained intracellular drug delivery
S Dhawan, S Ghosh, R Ravinder, SS Bais, S Basak, NMA Krishnan, ...
Bioconjugate chemistry 30 (9), 2458-2468, 2019
Learning the dynamics of particle-based systems with Lagrangian graph neural networks
R Bhattoo, S Ranu, NMA Krishnan
Machine Learning: Science and Technology 4 (1), 015003, 2023
Unravelling the performance of physics-informed graph neural networks for dynamical systems
A Thangamuthu, G Kumar, S Bishnoi, R Bhattoo, NM Krishnan, S Ranu
Advances in Neural Information Processing Systems 35, 3691-3702, 2022
Understanding the Compositional Control on Electrical, Mechanical, Optical, and Physical Properties of Inorganic Glasses with Interpretable Machine Learning
R Bhattoo, S Bishnoi, M Zaki, NMA Krishnan
Acta Materialia, 118439, 2022
Enhancing the Inductive Biases of Graph Neural ODE for Modeling Physical Systems
S Bishnoi, R Bhattoo, J Jayadeva, S Ranu, NMA Krishnan
The Eleventh International Conference on Learning Representations, 2023
A Peridynamics-Based Micromechanical Modeling Approach for Random Heterogeneous Structural Materials
S Nayak, R Ravinder, NM Krishnan, S Das
Materials 13 (6), 1298, 2020
Irradiation‐induced brittle‐to‐ductile transition in α‐quartz
R Ravinder, A Kumar, R Kumar, P Vangla, NMA Krishnan
Journal of the American Ceramic Society 103 (7), 3962-3970, 2020
Revealing the compositional control of electrical, mechanical, optical, and physical properties of inorganic glasses
R Ravinder, S Bishnoi, M Zaki, NM Krishnan
arXiv preprint arXiv:2103.12050, 2021
Lagrangian neural network with differentiable symmetries and relational inductive bias
R Bhattoo, S Ranu, NM Krishnan
arXiv preprint arXiv:2110.03266, 2021
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