| Harmless interpolation of noisy data in regression V Muthukumar, K Vodrahalli, V Subramanian, A Sahai IEEE Journal on Selected Areas in Information Theory 1 (1), 67-83, 2020 | 272 | 2020 |
| Disparities in dermatology AI performance on a diverse, curated clinical image set R Daneshjou, K Vodrahalli, RA Novoa, M Jenkins, W Liang, V Rotemberg, ... Science advances 8 (31), eabq6147, 2022 | 218 | 2022 |
| Serverless linear algebra V Shankar, K Krauth, K Vodrahalli, Q Pu, B Recht, I Stoica, ... Proceedings of the 11th ACM Symposium on Cloud Computing, 281-295, 2020 | 110 | 2020 |
| Can large language models provide useful feedback on research papers? A large-scale empirical analysis W Liang, Y Zhang, H Cao, B Wang, DY Ding, X Yang, K Vodrahalli, S He, ... NEJM AI 1 (8), AIoa2400196, 2024 | 84 | 2024 |
| Do humans trust advice more if it comes from ai? an analysis of human-ai interactions K Vodrahalli, R Daneshjou, T Gerstenberg, J Zou Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, 763-777, 2022 | 65 | 2022 |
| Are all training examples created equal? an empirical study K Vodrahalli, K Li, J Malik arXiv preprint arXiv:1811.12569, 2018 | 60 | 2018 |
| Adversarial training helps transfer learning via better representations Z Deng, L Zhang, K Vodrahalli, K Kawaguchi, JY Zou Advances in Neural Information Processing Systems 34, 25179-25191, 2021 | 55 | 2021 |
| 3D computer vision based on machine learning with deep neural networks: A review K Vodrahalli, AK Bhowmik Journal of the Society for Information Display 25 (11), 676-694, 2017 | 47 | 2017 |
| Disparities in dermatology ai: Assessments using diverse clinical images R Daneshjou, K Vodrahalli, W Liang, RA Novoa, M Jenkins, V Rotemberg, ... arXiv preprint arXiv:2111.08006, 2021 | 40 | 2021 |
| Uncalibrated models can improve human-ai collaboration K Vodrahalli, T Gerstenberg, JY Zou Advances in Neural Information Processing Systems 35, 4004-4016, 2022 | 37 | 2022 |
| TrueImage: a machine learning algorithm to improve the quality of telehealth photos K Vodrahalli, R Daneshjou, RA Novoa, A Chiou, JM Ko, J Zou BIOCOMPUTING 2021: Proceedings of the Pacific Symposium, 220-231, 2020 | 31 | 2020 |
| Can large language models provide useful feedback on research papers W Liang, Y Zhang, H Cao, B Wang, D Ding, X Yang, K Vodrahalli, S He, ... A large-scale empirical analysis. In arXiv preprint, 2023 | 27 | 2023 |
| Development and clinical evaluation of an artificial intelligence support tool for improving Telemedicine photo quality K Vodrahalli, J Ko, AS Chiou, R Novoa, A Abid, M Phung, K Yekrang, ... JAMA dermatology 159 (5), 496-503, 2023 | 11 | 2023 |
| Predicting visuo-motor diseases from eye tracking data K Vodrahalli, M Filipkowski, T Chen, J Zou, YJ Liao PACIFIC SYMPOSIUM ON BIOCOMPUTING 2022, 242-253, 2021 | 8 | 2021 |
| Are All Training Examples Created Equal K Vodrahalli, K Li, J Malik An Empirical Study. CoRR abs/1811.12569, 2018 | 7 | 2018 |
| Artwhisperer: A dataset for characterizing human-ai interactions in artistic creations K Vodrahalli, J Zou arXiv preprint arXiv:2306.08141, 2023 | 6 | 2023 |
| Some new numeric results concerning the Witsenhausen counterexample V Subramanian, L Brink, N Jain, K Vodrahalli, A Jalan, N Shinde, A Sahai 2018 56th Annual Allerton Conference on Communication, Control, and …, 2018 | 6 | 2018 |
| Learning to communicate in a noisy environment A Sahai, J Sanz, V Subramanian, C Tran, K Vodrahalli arXiv preprint arXiv:1910.09630, 2019 | 5 | 2019 |
| Blind interactive learning of modulation schemes: Multi-agent cooperation without co-design A Sahai, J Sanz, V Subramanian, C Tran, K Vodrahalli IEEE Access 8, 63790-63820, 2020 | 4 | 2020 |
| Learning to communicate with limited co-design A Sahai, J Sanz, V Subramanian, C Tran, K Vodrahalli 2019 57th Annual Allerton Conference on Communication, Control, and …, 2019 | 3 | 2019 |
