| A Survey on Neural Architecture Search M Wistuba, A Rawat, T Pedapati arXiv preprint arXiv:1905.01392, 2019 | 377 | 2019 |
| Foresight: Recommending visual insights Ç Demiralp, PJ Haas, S Parthasarathy, T Pedapati Proceedings of the VLDB Endowment 10 (12), 1937-1940, 2017 | 164* | 2017 |
| Model Agnostic Contrastive Explanations for Classification Models A Dhurandhar, T Pedapati, A Balakrishnan, PY Chen, K Shanmugam, ... IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2024 | 84* | 2024 |
| Understanding unequal gender classification accuracy from face images V Muthukumar, T Pedapati, N Ratha, P Sattigeri, CW Wu, B Kingsbury, ... arXiv preprint arXiv:1812.00099, 2018 | 61 | 2018 |
| Learning Global Transparent Models Consistent with Local Contrastive Explanations T Pedapati, A Balakrishnan, K Shanmugam, A Dhurandhar Advances in Neural Information Processing Systems 33, 2020 | 38 | 2020 |
| Learning to Rank Learning Curves M Wistuba, T Pedapati International Conference on Machine Learning, 10303-10312, 2020 | 28 | 2020 |
| Contrastive Explanations for Comparing Preferences of Reinforcement Learning J Gajcin, R Nair, T Pedapati, R Marinescu, E Daly, I Dusparic AAAI Conference on Artificial Intelligence, 2022 | 14* | 2022 |
| Creating optimized machine-learning models G Thomas, ACI Malossi, T Pedapati, G Venkataraman, R Istrate, ... US Patent App. 16/216,138, 2020 | 14 | 2020 |
| LakeBench: Benchmarks for Data Discovery over Data Lakes K Srinivas, J Dolby, I Abdelaziz, O Hassanzadeh, H Kokel, A Khatiwada, ... arXiv preprint arXiv:2307.04217, 2023 | 13 | 2023 |
| CoFrNets: interpretable neural architecture inspired by continued fractions I Puri, A Dhurandhar, T Pedapati, K Shanmugam, D Wei, KR Varshney Advances in neural information processing systems 34, 21668-21680, 2021 | 13 | 2021 |
| Inductive Transfer for Neural Architecture Optimization M Wistuba, T Pedapati arXiv preprint arXiv:1903.03536, 2019 | 13 | 2019 |
| NeuNetS: An Automated Synthesis Engine for Neural Network Design A Sood, B Elder, B Herta, C Xue, C Bekas, ACI Malossi, D Saha, ... arXiv preprint arXiv:1901.06261, 2019 | 13 | 2019 |
| AutoText: An End-to-End AutoAI Framework for Text A Chaudhary, A Issak, K Kate, Y Katsis, A Valente, D Wang, A Evfimievski, ... Proceedings of the AAAI Conference on Artificial Intelligence 35 (18), 16001 …, 2021 | 9 | 2021 |
| Survey on automated end-to-end data science? D Bouneffouf, C Aggarwal, T Hoang, U Khurana, H Samulowitz, ... 2020 International Joint Conference on Neural Networks (IJCNN), 1-9, 2020 | 9 | 2020 |
| Dataset evolver: An interactive feature engineering notebook F Nargesian, U Khurana, T Pedapati, H Samulowitz, D Turaga Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 8 | 2018 |
| Extracting Patient Information from an Electronic Medical Record JJ Liang, T Pedapati, JM Prager US Patent App. 15/403,363, 2018 | 7 | 2018 |
| Neurology-as-a-Service for the Developing World T Dharamsi, P Das, T Pedapati, G Bramble, V Muthusamy, H Samulowitz, ... arXiv preprint arXiv:1711.06195, 2017 | 7 | 2017 |
| MILO: Model-Agnostic Subset Selection Framework for Efficient Model Training and Tuning K Killamsetty, AV Evfimievski, T Pedapati, K Kate, L Popa, R Iyer arXiv preprint arXiv:2301.13287, 2023 | 6 | 2023 |
| Model agnostic contrastive explanations for structured data A Dhurandhar, PY Chen, K Shanmugam, T Pedapati, A Balakrishnan, ... US Patent 11,507,787, 2022 | 5 | 2022 |
| From PEFT to DEFT: Parameter Efficient Finetuning for Reducing Activation Density in Transformers B Runwal, T Pedapati, PY Chen arXiv preprint arXiv:2402.01911, 2024 | 4 | 2024 |
