| Fastshap: Real-time shapley value estimation N Jethani, M Sudarshan, IC Covert, SI Lee, R Ranganath International conference on learning representations, 2021 | 156 | 2021 |
| Have we learned to explain?: How interpretability methods can learn to encode predictions in their interpretations. N Jethani, M Sudarshan, Y Aphinyanaphongs, R Ranganath International Conference on Artificial Intelligence and Statistics, 1459-1467, 2021 | 73 | 2021 |
| A validated, real-time prediction model for favorable outcomes in hospitalized COVID-19 patients N Razavian, VJ Major, M Sudarshan, J Burk-Rafel, P Stella, H Randhawa, ... NPJ digital medicine 3 (1), 130, 2020 | 67 | 2020 |
| Machine learning improved classification of psychoses using clinical and biological stratification: update from the bipolar-schizophrenia network for intermediate phenotypes (B … SS Mothi, M Sudarshan, N Tandon, C Tamminga, G Pearlson, J Sweeney, ... Schizophrenia research 214, 60-69, 2019 | 31 | 2019 |
| Deep direct likelihood knockoffs M Sudarshan, W Tansey, R Ranganath Advances in neural information processing systems 33, 5036-5046, 2020 | 25 | 2020 |
| Deep dreaming, aberrant salience and psychosis: connecting the dots by artificial neural networks MS Keshavan, M Sudarshan Schizophrenia research 188, 178-181, 2017 | 19 | 2017 |
| Deciphering RNA splicing logic with interpretable machine learning SE Liao, M Sudarshan, O Regev Proceedings of the National Academy of Sciences 120 (41), e2221165120, 2023 | 10 | 2023 |
| 14–3‐3γ prevents centrosome duplication by inhibiting NPM1 function A Bose, K Modi, S Dey, S Dalvi, P Nadkarni, M Sudarshan, TK Kundu, ... Genes to Cells 26 (6), 426-446, 2021 | 10 | 2021 |
| Design and development of a self-stabilizing, autonomous sailboat with zero-net stored-energy use R Baker, L Kambourian, S Hajarian, T Augenstein, S Harnett, GM Lee, ... Robotic Sailing 2015: Proceedings of the 8th International Robotic Sailing …, 2016 | 9 | 2016 |
| Development and external validation of a dynamic risk score for early prediction of cardiogenic shock in cardiac intensive care units using machine learning Y Hu, A Lui, M Goldstein, M Sudarshan, A Tinsay, C Tsui, SD Maidman, ... European Heart Journal: Acute Cardiovascular Care 13 (6), 472-480, 2024 | 7 | 2024 |
| Fast kernel-based association testing of non-linear genetic effects for biobank-scale data B Fu, A Pazokitoroudi, M Sudarshan, Z Liu, L Subramanian, ... Nature communications 14 (1), 4936, 2023 | 6 | 2023 |
| Machine learning for discovery: deciphering RNA splicing logic SE Liao, M Sudarshan, O Regev bioRxiv, 2022.10. 01.510472, 2022 | 5 | 2022 |
| Contra: Contrarian statistics for controlled variable selection M Sudarshan, A Puli, L Subramanian, S Sankararaman, R Ranganath International conference on artificial intelligence and statistics, 1900-1908, 2021 | 4 | 2021 |
| A validated, real-time prediction model for favorable outcomes in hospitalized COVID-19 patients. NPJ Digit Med. 2020; 3: 130 N Razavian, VJ Major, M Sudarshan, J Burk-Rafel, P Stella, H Randhawa, ... | 4 | |
| DIET: Conditional independence testing with marginal dependence measures of residual information M Sudarshan, A Puli, W Tansey, R Ranganath International Conference on Artificial Intelligence and Statistics, 10343-10367, 2023 | 3 | 2023 |
| On the feasibility of machine learning augmented magnetic resonance for point-of-care identification of disease R Singhal, M Sudarshan, A Mahishi, S Kaushik, L Ginocchio, A Tong, ... arXiv preprint arXiv:2301.11962, 2023 | 3 | 2023 |
| A dynamic risk score for early prediction of cardiogenic shock using machine learning Y Hu, A Lui, M Goldstein, M Sudarshan, A Tinsay, C Tsui, S Maidman, ... arXiv preprint arXiv:2303.12888, 2023 | 1 | 2023 |
| Accelerated MR screenings with direct k-space classification R Singhal, M Sudarshan, L Ginocchio, A Tong, H Chandarana, ... Joint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting (London, 7–12 …, 2022 | 1 | 2022 |
| Investigations on Compression Behaviour of Short Reinforced NSC Columns J Sanjith, R Prabhakara, MS Sudarshan, Jayachandra Sustainability Trends and Challenges in Civil Engineering: Select …, 2022 | | 2022 |
| On Deep Learning Tools for Scientific Discovery in Healthcare M Sudarshan New York University, 2022 | | 2022 |
Rajesh RanganathAssistant Professor, NYUEmail yang diverifikasi di cs.princeton.edu
