| Data-free parameter pruning for deep neural networks S Srinivas, RV Babu British Machine Vision Conference (BMVC), 2015 | 711 | 2015 |
| A taxonomy of deep convolutional neural nets for computer vision S Srinivas, RK Sarvadevabhatla, KR Mopuri, N Prabhu, SSS Kruthiventi, ... Frontiers in Robotics and AI 2, 172022, 2016 | 355* | 2016 |
| Full-gradient representation for neural network visualization S Srinivas, F Fleuret Neural Information Processing Systems (NeurIPS), 2019 | 339 | 2019 |
| Training sparse neural networks S Srinivas, A Subramanya, R Venkatesh Babu CVPR Embedded Vision Workshop, 138-145, 2017 | 251 | 2017 |
| Knowledge Transfer with Jacobian Matching S Srinivas, F Fleuret International Conference on Machine Learning (ICML), 2018 | 202 | 2018 |
| Certifying llm safety against adversarial prompting A Kumar, C Agarwal, S Srinivas, AJ Li, S Feizi, H Lakkaraju arXiv preprint arXiv:2309.02705, 2023 | 155 | 2023 |
| Which explanation should i choose? a function approximation perspective to characterizing post hoc explanations T Han, S Srinivas, H Lakkaraju Neural Information Processing Systems (NeurIPS), 2022 | 98 | 2022 |
| Estimating Confidence for Deep Neural Networks through Density modeling A Subramanya, S Srinivas, RV Babu 2018 International Conference on Signal Processing and Communications (SPCOM …, 2018 | 68* | 2018 |
| Rethinking the Role of Gradient Based Attribution Methods for Model Interpretability S Srinivas, F Fleuret International Conference on Learning Representations (ICLR), 2021 | 53 | 2021 |
| Generalized dropout S Srinivas, RV Babu Tech Report, 2016 | 51 | 2016 |
| Learning the architecture of deep neural networks S Srinivas, RV Babu British Machine Vision Conference (BMVC), 2016 | 48* | 2016 |
| Interpreting clip with sparse linear concept embeddings (splice) U Bhalla, A Oesterling, S Srinivas, FP Calmon, H Lakkaraju arXiv preprint arXiv:2402.10376, 2024 | 23 | 2024 |
| Efficient Training of Low-Curvature Neural Networks S Srinivas, K Matoba, H Lakkaraju, F Fleuret Neural Information Processing Systems (NeurIPS), 2022 | 23 | 2022 |
| Data-efficient structured pruning via submodular optimization M El Halabi, S Srinivas, S Lacoste-Julien Neural Information Processing Systems (NeurIPS), 2022 | 20 | 2022 |
| Cyclical Pruning for Sparse Neural Networks S Srinivas, A Kuzmin, M Nagel, M van Baalen, A Skliar, T Blankevoort CVPR Workshop on Efficient Deep Learning for Computer Vision, 2022 | 19 | 2022 |
| Discriminative feature attributions: bridging post hoc explainability and inherent interpretability U Bhalla, S Srinivas, H Lakkaraju Advances in neural information processing systems 36, 44105-44122, 2023 | 14* | 2023 |
| Which models have perceptually-aligned gradients? an explanation via off-manifold robustness S Srinivas, S Bordt, H Lakkaraju Advances in neural information processing systems 36, 21172-21195, 2023 | 13 | 2023 |
| Compensating for large in-plane rotations in natural images L Boominathan, S Srinivas, RV Babu Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP), 2016 | 7 | 2016 |
| Word-level explanations for analyzing bias in text-to-image models A Lin, LM Paes, SH Tanneru, S Srinivas, H Lakkaraju arXiv preprint arXiv:2306.05500, 2023 | 6 | 2023 |
| On Minimizing the impact of dataset shifts on actionable explanations AP Meyer, D Ley, S Srinivas, H Lakkaraju Uncertainty in Artificial Intelligence, 1434-1444, 2023 | 5 | 2023 |
R. Venkatesh BabuCDS, Indian Institute of Science, Bangalore, Indiaایمیل تأیید شده در iisc.ac.in