| Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ... arXiv preprint arXiv:2403.05530, 2024 | 447 | 2024 |
| Charting the right manifold: Manifold mixup for few-shot learning P Mangla, N Kumari, A Sinha, M Singh, B Krishnamurthy, ... Proceedings of the IEEE/CVF winter conference on applications of computer …, 2020 | 407 | 2020 |
| D2c: Diffusion-decoding models for few-shot conditional generation A Sinha, J Song, C Meng, S Ermon Advances in Neural Information Processing Systems 34, 12533-12548, 2021 | 132 | 2021 |
| Negative data augmentation A Sinha, K Ayush, J Song, B Uzkent, H Jin, S Ermon arXiv preprint arXiv:2102.05113, 2021 | 129 | 2021 |
| Harnessing the vulnerability of latent layers in adversarially trained models N Kumari, M Singh, A Sinha, H Machiraju, B Krishnamurthy, ... Proceedings of the 28th International Joint Conference on Artificial …, 2019 | 71* | 2019 |
| Intelligent fault analysis in electrical power grids B Bhattacharya, A Sinha 2017 IEEE 29th International Conference on Tools with Artificial …, 2017 | 69 | 2017 |
| Attributional robustness training using input-gradient spatial alignment M Singh, N Kumari, P Mangla, A Sinha, VN Balasubramanian, ... European Conference on Computer Vision, 515-533, 2020 | 31* | 2020 |
| Introspection: Accelerating neural network training by learning weight evolution A Sinha, M Sarkar, A Mukherjee, B Krishnamurthy arXiv preprint arXiv:1704.04959, 2017 | 27 | 2017 |
| Powering robust fashion retrieval with information rich feature embeddings A Chopra, A Sinha, H Gupta, M Sarkar, K Ayush, B Krishnamurthy Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 24 | 2019 |
| Comparing distributions by measuring differences that affect decision making S Zhao, A Sinha, Y He, A Perreault, J Song, S Ermon International Conference on Learning Representations, 2022 | 23 | 2022 |
| On the benefits of models with perceptually-aligned gradients G Aggarwal, A Sinha, N Kumari, M Singh arXiv preprint arXiv:2005.01499, 2020 | 14 | 2020 |
| A method for computing class-wise universal adversarial perturbations T Gupta, A Sinha, N Kumari, M Singh, B Krishnamurthy arXiv preprint arXiv:1912.00466, 2019 | 14 | 2019 |
| Neural networks in an adversarial setting and ill-conditioned weight space A Sinha, M Singh, B Krishnamurthy Joint European Conference on Machine Learning and Knowledge Discovery in …, 2018 | 14 | 2018 |
| Generating trained neural networks with increased robustness against adversarial attacks M Singh, N Kumari, D Khattar, B Krishnamurthy, A Sinha US Patent 11,481,617, 2022 | 13 | 2022 |
| Introspection network for training neural networks M Sarkar, B Krishnamurthy, A Sinha, A Mukherjee US Patent 10,755,199, 2020 | 13 | 2020 |
| Attention based natural language grounding by navigating virtual environment A Sinha, B Akilesh, M Sarkar, B Krishnamurthy 2019 IEEE Winter Conference on Applications of Computer Vision (WACV), 236-244, 2019 | 13 | 2019 |
| Identifying digital attributes from multiple attribute groups within target digital images utilizing a deep cognitive attribution neural network A Chopra, M Sarkar, J Dahl, H Gupta, B Krishnamurthy, A Sinha US Patent 11,386,144, 2022 | 6 | 2022 |
| Intelligent subset selection of power generators for economic dispatch B Bhattacharya, A Sinha arXiv preprint arXiv:1709.02513, 2017 | 6 | 2017 |
| Classifying digital images in few-shot tasks based on neural networks trained using manifold mixup regularization and self-supervision M Singh, P Mangla, N Kumari, B Krishnamurthy, A Sinha US Patent 11,308,353, 2022 | 5 | 2022 |
| Deep fault analysis and subset selection in solar power grids B Bhattacharya, A Sinha arXiv preprint arXiv:1711.02810, 2017 | 5 | 2017 |
Balaji KrishnamurthyAdobe IncVerified email at adobe.com
