| " You might also like this model": Data Driven Approach for Recommending Deep Learning Models for Unknown Image Datasets A Prabhu, R Dasgupta, A Sankaran, S Tamilselvam, S Mani arXiv preprint arXiv:1911.11433, 2019 | | 2019 |
| A flexible approach for securing MANETs A Prabhu, R Dhanaraj International Conference on Recent Advances and Innovations in Engineering …, 2014 | 3 | 2014 |
| Adversary is the best teacher: towards extremely compact neural networks A Prabhu, H Krishna, S Saha Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | | 2018 |
| Analysis of the observations of solar magnetic helicity A Prabhu Solar Helicities in Theory and Observations: Implications for Space Weather …, 2019 | | 2019 |
| Deep Expander Networks A Prabhu, G Varma, A Namboodiri | | |
| Deep expander networks: Efficient deep networks from graph theory A Prabhu, G Varma, A Namboodiri Proceedings of the European Conference on Computer Vision (ECCV), 20-35, 2018 | 86 | 2018 |
| Distilling large language models into tiny and effective students using pqrnn AS Prabhu Kaliamoorthi, E Li, M Johnson CoRR, abs/2101.08890, 2021 | 12 | 2021 |
| Distribution-aware binarization of neural networks for sketch recognition A Prabhu, V Batchu, SA Munagala, R Gajawada, A Namboodiri 2018 IEEE Winter Conference on Applications of Computer Vision (WACV), 830-838, 2018 | 3 | 2018 |
| Evaluating Inexact Unlearning Requires Revisiting Forgetting S Goel, A Prabhu, P Kumaraguru arXiv preprint arXiv:2201.06640, 2022 | 10 | 2022 |
| Exploring Binarization and Pruning of Convolutional Neural Networks A Prabhu International Institute of Information Technology Hyderabad, 2019 | | 2019 |
| Gdumb: A simple approach that questions our progress in continual learning A Prabhu, PHS Torr, PK Dokania European conference on computer vision, 524-540, 2020 | 543 | 2020 |
| Helicity proxies from linear polarisation of solar active regions A Prabhu, A Brandenburg, MJ Käpylä, A Lagg Astronomy & Astrophysics 641, A46, 2020 | 5 | 2020 |
| Hunting down the cause of solar magnetism M Viviani, A Prabhu, J Warnecke, L Duarte, J Pekkilä, M Rheinhardt, ... arXiv preprint arXiv:2102.03168, 2021 | | 2021 |
| Hybrid binary networks: optimizing for accuracy, efficiency and memory A Prabhu, V Batchu, R Gajawada, SA Munagala, A Namboodiri 2018 IEEE Winter Conference on Applications of Computer Vision (WACV), 821-829, 2018 | 17 | 2018 |
| Inferring magnetic helicity spectrum in spherical domains AP Prabhu, NK Singh, MJ Käpylä, A Lagg EDP SCIENCES, 2021 | | 2021 |
| Inferring magnetic helicity spectrum in spherical domains: Method and example applications AP Prabhu, NK Singh, MJ Käpylä, A Lagg Astronomy & Astrophysics 654, A3, 2021 | 4 | 2021 |
| Learning clustered sub-spaces for sketch-based image retrieval K Ghosal, A Prabhu, R Dasgupta, AM Namboodiri 2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR), 599-603, 2015 | 1 | 2015 |
| Machine Learning Systems and Methods for Evaluating Sampling Bias in Deep Active Classification A Prabhu, C Dognin, MK Singh US Patent App. 16/919,898, 2021 | 4 | 2021 |
| No cost likelihood manipulation at test time for making better mistakes in deep networks S Karthik, A Prabhu, PK Dokania, V Gandhi arXiv preprint arXiv:2104.00795, 2021 | 15 | 2021 |
| Pest science and management S Saha, FE Nwilene, O Okhidievbie, TA Agunbiade, AK Traore, ... International Rice Research Notes 34, 2009 | | 2009 |
