| Including crystal structure attributes in machine learning models of formation energies via Voronoi tessellations L Ward, R Liu, A Krishna, VI Hegde, A Agrawal, A Choudhary, ... Physical Review B 96 (2), 024104, 2017 | 347 | 2017 |
| Predicting the outcome of startups: less failure, more success A Krishna, A Agrawal, A Choudhary 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW …, 2016 | 179 | 2016 |
| Machine-learning-accelerated high-throughput materials screening: Discovery of novel quaternary Heusler compounds K Kim, L Ward, J He, A Krishna, A Agrawal, C Wolverton Physical Review Materials 2 (12), 123801, 2018 | 99 | 2018 |
| Polarity trend analysis of public sentiment on YouTube A Krishna, J Zambreno, S Krishnan Proceedings of the 19th international conference on management of data, 125-128, 2013 | 40 | 2013 |
| Influence of different types of soils on soil-geosynthetics interaction behavior AK Choudhary, AM Krishna IJIRSET 3 (SPI 4), 60-68, 2014 | 7 | 2014 |
| Polarity trend analysis of public sentiment on YouTube A Krishna | 4 | 2014 |
| Accelerated discovery of quaternary Heusler with high-throughput density functional theory and machine learning K Kim, L Ward, J He, A Krishna, A Agrawal, P Voorhees, C Wolverton APS March Meeting Abstracts 2018, R12. 005, 2018 | 2 | 2018 |
| Accurate models of formation enthalpy created using machine learning and voronoi tessellations L Ward, R Liu, A Krishna, V Hegde, A Agrawal, A Choudhary, C Wolverton APS March Meeting Abstracts 2016, E22. 010, 2016 | 1 | 2016 |
