| Platelet microparticle-inspired clot-responsive nanomedicine for targeted fibrinolysis CL Pawlowski, W Li, M Sun, K Ravichandran, DS Hickman, C Kos, G Kaur, ... Biomaterials 128, 94-108, 2017 | 145 | 2017 |
| A deep learning classifier for prediction of pathological complete response to neoadjuvant chemotherapy from baseline breast DCE-MRI K Ravichandran, N Braman, A Janowczyk, A Madabhushi Medical imaging 2018: computer-aided diagnosis 10575, 79-88, 2018 | 69 | 2018 |
| Implicit Bias of the Step Size in Linear Diagonal Neural Networks MS Nacson, K Ravichandran, N Srebro, D Soudry International Conference on Machine Learning, 16270-16295, 2022 | 38 | 2022 |
| Predicting pathological complete response to neoadjuvant chemotherapy from baseline breast dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) A Madabhushi, N Braman, A Janowczyk, K Ravichandran US Patent 10,902,591, 2021 | 4 | 2021 |
| Using effective dimension to analyze feature transformations in deep neural networks K Ravichandran, A Jain, A Rakhlin ICML 2019 Workshop on Identifying and Understanding Deep Learning Phenomena, 2019 | 4 | 2019 |
| Predicting neo-adjuvant chemotherapy response from pre-treatment breast MRI using machine learning and HER2 status. N Braman, K Ravichandran, A Janowczyk, J Abraham, A Madabhushi Journal of Clinical Oncology 36 (15_suppl), 582-582, 2018 | 3 | 2018 |
| Yellow Fever in Brazil: Using Novel Data Sources to Produce Localized Policy Recommendations S De Silva, R Pinnamaneni, K Ravichandran, A Fadaq, Y Mei, V Sin Leveraging Data Science for Global Health, 417-428, 2020 | 1 | 2020 |
| Predicting neo-adjuvant chemotherapy response from pre-treatment breast magnetic resonance imaging using artificial intelligence and her2 status A Madabhushi, N Braman, K Ravichandran, A Janowczyk US Patent App. 16/280,322, 2019 | 1 | 2019 |
| Nearly-tight Approximation Guarantees for the Improving Multi-Armed Bandits Problem A Blum, K Ravichandran arXiv preprint arXiv:2404.01198, 2024 | | 2024 |
| Applying statistical learning theory to deep learning C Gerbelot, A Karagulyan, S Karp, K Ravichandran, M Stern, N Srebro arXiv preprint arXiv:2311.15404, 2023 | | 2023 |
| Learning from setbacks: the impact of adversarial initialization on generalization performance K Ravichandran, Y Dandi, S Karp, F Mignacco NeurIPS 2023 Workshop on Mathematics of Modern Machine Learning, 2023 | | 2023 |
| Testing Tail Weight of a Distribution Via Hazard Rate M Aliakbarpour, AS Biswas, K Ravichandran, R Rubinfeld International Conference on Algorithmic Learning Theory, 34-81, 2023 | | 2023 |
| An algorithm for testing heavy-tailed distributions K Ravichandran Massachusetts Institute of Technology, 2020 | | 2020 |
