Publications

Books:

• • Latex and HTML, ISBN -  978-81-928184-6-7, Year - 2016, Publisher Vardhman Publications, Delhi.

  • Graph Theory, ISBN – 978-81-928184-4-3, Year – 2015, Publisher – Vardhman Publications, Delhi.

  • Practical using Mathematica for Calculus-I, ISBN – 978-81-928184-3-6, Year – 2014, Publisher – Vardhman Publications, Delhi.

  • Practical using Mathematica for Numerical Methods and Analysis - II, ISBN - 978-81-928184-2-9, Year – 2014, Publisher – Vardhman Publications, Delhi.

Papers:

• Sandeep Kumar, Koushik Biswas, and Ashish Kumar Pandey, Prediction of landfall intensity, location, and time of a tropical cyclone. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 35. 2021.

• Sandeep Kumar, Koushik Biswas, and Ashish Kumar Pandey, Predicting landfall’s location and time of a tropical cyclone using reanalysis data. In Artificial Neural Networks and Machine Learning – ICANN 2021. Springer International Publishing, 2021. ISBN 978-3-030-86380-7.

• Sandeep Kumar, Koushik Biswas, and Ashish Kumar Pandey, Track prediction of tropical cyclones using long short-term memory network. In 2021 IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC) 2021.

• Sandeep Kumar, Koushik Biswas, and Ashish Kumar Pandey, Will a tropical cyclone make landfall?. Neural Computing and Applications 35, 5807–5818 (2023). https://doi.org/10.1007/s00521-022-07996-7 .

• Biswas, K., Kumar, S., Banerjee, S., & Pandey, A. K. (2022). Smooth maximum unit: Smooth activation function for deep networks using smoothing maximum technique. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 794-803). 

• Biswas, K., Kumar, S., Banerjee, S., & Pandey, A. K. (2022, June). ErfAct and Pserf: Non-monotonic Smooth Trainable Activation Functions. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 36, No. 6, pp. 6097-6105). 

• Biswas, K., Kumar, S., Banerjee, S., & Pandey, A. K. (2021). TanhSoft—dynamic trainable activation functions for faster learning and better performance. IEEE Access, 9, 120613-120623. 

• Chang, D., Chauhan, A. K., Kumar, S., & Sanadhya, S. K. (2018, March). Revocable identity-based encryption from codes with rank metric. In Cryptographers’ Track at the RSA Conference (pp. 435-451). Cham: Springer International Publishing. 

• Biswas, K., Kumar, S., Banerjee, S., & Pandey, A. K. (2021). Eis-efficient and trainable activation functions for better accuracy and performance. In Artificial Neural Networks and Machine Learning–ICANN 2021: 30th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 14–17, 2021, Proceedings, Part II 30 (pp. 260-272). Springer International Publishing. 

• Kumar, S., Biswas, K., & Pandey, A. K. (2022). Forecasting formation of a Tropical Cyclone Using Reanalysis Data. arXiv preprint arXiv:2212.06149.