| Using deep and convolutional neural networks for accurate emotion classification on deap dataset. S Tripathi, S Acharya, RD Sharma, S Mittal, S Bhattacharya Twenty-Ninth IAAI Conference, 2017, AAAI, 4746-4752, 2017 | 390* | 2017 |
| Multi-Modal Emotion Recognition on IEMOCAP with Neural Networks. S Tripathi, S Tripathi, H Beigi arXiv preprint arXiv:1804.05788, 2018 | 204* | 2018 |
| A survey of on-device machine learning: An algorithms and learning theory perspective S Dhar, J Guo, J Liu, S Tripathi, U Kurup, M Shah ACM Transactions on Internet of Things 2 (3), 1-49, 2021 | 160 | 2021 |
| Pruning algorithms to accelerate convolutional neural networks for edge applications: A survey J Liu, S Tripathi, U Kurup, M Shah arXiv preprint arXiv:2005.04275, 2020 | 47 | 2020 |
| Predicting online doctor ratings from user reviews using convolutional neural networks RD Sharma, S Tripathi, SK Sahu, S Mittal, A Anand International Journal of Machine Learning and Computing 6 (2), 149, 2016 | 32 | 2016 |
| Auptimizer - an Extensible, Open-Source Framework for Hyperparameter Tuning J Liu, S Tripathi, U Kurup, M Shah 2019 IEEE International Conference on Big Data (Big Data), pp. 339-348., 2019 | 24 | 2019 |
| Using modern neural networks to predict the decisions of supreme court of the united states with state-of-the-art accuracy RD Sharma, S Mittal, S Tripathi, S Acharya Neural Information Processing: 22nd International Conference, ICONIP 2015 …, 2015 | 15 | 2015 |
| A unified web interface for the internet of things K Kumar, J Bose, S Tripathi 2016 IEEE Annual India Conference (INDICON), 1-6, 2016 | 8 | 2016 |
| Learnable graph inception network for emotion recognition A Shirian, S Tripathi, T Guha arXiv preprint arXiv:2008.02661, 2020 | 7 | 2020 |
| On-device machine learning: An algorithms and learning theory perspective. arXiv 2019 S Dhar, J Guo, J Liu, S Tripathi, U Kurup, M Shah arXiv preprint arXiv:1911.00623, 0 | 5 | |
| Training a neural network using periodic sampling over model weights S Tripathi, J Liu, U Kurup, M Shah US Patent 11,922,316, 2024 | 3 | 2024 |
| Make (nearly) every neural network better: Generating neural network ensembles by weight parameter resampling J Liu, S Tripathi, U Kurup, M Shah arXiv preprint arXiv:1807.00847, 2018 | 3 | 2018 |
| Universum GANs: Improving GANs through contradictions S Dhar, J Heydari, S Tripathi, U Kurup, M Shah arXiv preprint arXiv:2106.09946, 2021 | 2 | 2021 |
| Method for fast and accurate extraction of key information from webpages SG Kasi, S Tripathi 2016 IEEE International Conference on Web Services (ICWS), 500-505, 2016 | 2 | 2016 |
| Improving Model Training by Periodic Sampling over Weight Distributions S Tripathi, J Liu, S Dhar, U Kurup, M Shah 2020 IEEE International Conference on Big Data (Big Data), 112-122, 2020 | 1* | 2020 |
| Towards deeper generative architectures for GANs using dense connections S Tripathi, R Tu arXiv preprint arXiv:1804.11031, 2018 | 1 | 2018 |
| Evolving GANs: When Contradictions Turn into Compliance S Dhar, J Heydari, S Tripathi, U Kurup, M Shah arXiv preprint arXiv:2106.09946, 2021 | | 2021 |
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