| Smooth maximum unit: Smooth activation function for deep networks using smoothing maximum technique K Biswas, S Kumar, S Banerjee, AK Pandey Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 28 | 2022 |
| SMU: smooth activation function for deep networks using smoothing maximum technique K Biswas, S Kumar, S Banerjee, AK Pandey arXiv preprint arXiv:2111.04682, 2021 | 26 | 2021 |
| TanhSoft—dynamic trainable activation functions for faster learning and better performance K Biswas, S Kumar, S Banerjee, AK Pandey IEEE Access 9, 120613-120623, 2021 | 13 | 2021 |
| Erfact and pserf: Non-monotonic smooth trainable activation functions K Biswas, S Kumar, S Banerjee, AK Pandey Proceedings of the AAAI Conference on Artificial Intelligence 36 (6), 6097-6105, 2022 | 12 | 2022 |
| Revocable identity-based encryption from codes with rank metric D Chang, AK Chauhan, S Kumar, SK Sanadhya Cryptographers’ Track at the RSA Conference, 435-451, 2018 | 11 | 2018 |
| Prediction of landfall intensity, location, and time of a tropical cyclone S Kumar, K Biswas, AK Pandey Proceedings of the AAAI Conference on Artificial Intelligence 35 (17), 14831 …, 2021 | 7 | 2021 |
| Eis-efficient and trainable activation functions for better accuracy and performance K Biswas, S Kumar, S Banerjee, AK Pandey Artificial Neural Networks and Machine Learning–ICANN 2021: 30th …, 2021 | 7 | 2021 |
| SAU: Smooth activation function using convolution with approximate identities K Biswas, S Kumar, S Banerjee, A Kumar Pandey European Conference on Computer Vision, 313-329, 2022 | 6 | 2022 |
| Track prediction of tropical cyclones using long short-term memory network S Kumar, K Biswas, AK Pandey 2021 IEEE 11th Annual Computing and Communication Workshop and Conference …, 2021 | 6 | 2021 |
| Intensity prediction of tropical cyclones using long short-term memory network K Biswas, S Kumar, AK Pandey arXiv preprint arXiv:2107.03187, 2021 | 5 | 2021 |
| Tropical cyclone intensity estimations over the Indian ocean using machine learning K Biswas, S Kumar, AK Pandey arXiv preprint arXiv:2107.05573, 2021 | 3 | 2021 |
| Predicting landfall’s location and time of a tropical cyclone using reanalysis data S Kumar, K Biswas, AK Pandey Artificial Neural Networks and Machine Learning–ICANN 2021: 30th …, 2021 | 3 | 2021 |
| Will a tropical cyclone make landfall? S Kumar, K Biswas, AK Pandey Neural Computing and Applications 35 (8), 5807-5818, 2023 | 1 | 2023 |
| Forecasting formation of a Tropical Cyclone Using Reanalysis Data S Kumar, K Biswas, AK Pandey arXiv preprint arXiv:2212.06149, 2022 | | 2022 |
| ErfAct: Non-monotonic smooth trainable Activation Functions K Biswas, S Kumar, S Banerjee, AK Pandey arXiv preprint arXiv:2109.04386, 2021 | | 2021 |
| Prediction of Landfall Intensity, Location, and Time of a Tropical Cyclone AKP Sandeep Kumar, Koushik Biswas AAAI Special Track on AI for Social Impact 2021 35 (17), 14831-14839, 2021 | | 2021 |
| EIS--a family of activation functions combining Exponential, ISRU, and Softplus K Biswas, S Kumar, S Banerjee, AK Pandey arXiv preprint arXiv:2009.13501, 2020 | | 2020 |
Koushik BiswasIIIT DelhiVerified email at iiitd.ac.in
