| 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 | 93 | 2019 |
| Deep learning aided rational design of oxide glasses R Ravinder, KH Sridhara, S Bishnoi, HS Grover, M Bauchy, H Kodamana, ... Materials horizons 7 (7), 1819-1827, 2020 | 69* | 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 | 42 | 2021 |
| 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 242, 118439, 2023 | 38* | 2023 |
| Artificial intelligence and machine learning in glass science and technology: 21 challenges for the 21st century Ravinder, V Venugopal, S Bishnoi, S Singh, M Zaki, HS Grover, M Bauchy, ... International journal of applied glass science 12 (3), 277-292, 2021 | 34 | 2021 |
| 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 | 33 | 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 | 27 | 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, 2022 | 27* | 2022 |
| 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 | 26* | 2020 |
| Glass hardness: Predicting composition and load effects via symbolic reasoning-informed machine learning S Mannan, M Zaki, S Bishnoi, DR Cassar, J Jiusti, JCF Faria, ... Acta Materialia 255, 119046, 2023 | 14 | 2023 |
| Scalable Gaussian processes for predicting the optical, physical, thermal, and mechanical properties of inorganic glasses with large datasets, Mater. Adv. 2 (2021) 477–487 S Bishnoi, R Ravinder, HS Grover, H Kodamana, NMA Krishnan Royal Society of Chemistry. https://doi. org/10.1039/D0MA00764A.[Online …, 2021 | 9 | 2021 |
| Discovering symbolic laws directly from trajectories with hamiltonian graph neural networks S Bishnoi, R Bhattoo, S Ranu, NMA Krishnan Machine Learning: Science and Technology 5 (3), 035049, 2024 | 6* | 2024 |
| Predicting oxide glass properties with low complexity neural network and physical and chemical descriptors S Bishnoi, S Badge, NMA Krishnan Journal of Non-Crystalline Solids 616, 122488, 2023 | 5 | 2023 |
| BroGNet: Momentum-Conserving Graph Neural Stochastic Differential Equation for Learning Brownian Dynamics S Bishnoi, J Jayadeva, S Ranu, NMA Krishnan The Twelfth International Conference on Learning Representations, 2024 | 3* | 2024 |
| Geometric optics based analysis of radiation heat transfer in glass melting furnace foams..... 337 VV Ravinder, S Bishnoi, S Singh, M Zaki, HS Grover, M Bauchy, ... Artificial intelligence 12 (3), 2021 | | 2021 |
N. M. Anoop KrishnanAssociate Professor, Indian Institute of Technology DelhiVerified email at iitd.ac.in
