| 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 Computer Society Conference on Computer Vision and …, 2022 | 90* | 2022 |
| 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 | 28* | 2021 |
| Revisiting the use of squared magnitude function for the optimal approximation of (1+ α)-order Butterworth filter S Mahata, S Banerjee, R Kar, D Mandal AEU-International Journal of Electronics and Communications 110, 152826, 2019 | 19 | 2019 |
| 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 | 17 | 2022 |
| Real-analytic AbC constructions on the torus S Banerjee, P Kunde Ergodic Theory and Dynamical Systems 39 (10), 2643-2688, 2019 | 16 | 2019 |
| Non-standard real-analytic realizations of some rotations of the circle S Banerjee Ergodic Theory and Dynamical Systems 37 (5), 1369-1386, 2017 | 14 | 2017 |
| 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 | 13 | 2022 |
| Real-analytic realization of Uniform Circular Systems and some applications S Banerjee, P Kunde Journal d'Analyse Mathématique 148 (2), 399-445, 2022 | 9* | 2022 |
| EIS-Efficient and Trainable Activation Functions for Better Accuracy and Performance K Biswas, S Kumar, S Banerjee, AK Pandey 30th International Conference on Artificial Neural Networks, 2021 | 9 | 2021 |
| Orthogonal-Pad\'e Activation Functions: Trainable Activation functions for smooth and faster convergence in deep networks K Biswas, S Banerjee, AK Pandey arXiv preprint arXiv:2106.09693, 2021 | 5 | 2021 |
| Slow entropy of some combinatorial constructions S Banerjee, P Kunde, D Wei Nonlinearity 36 (6), 2923 - 2974, 2023 | 3 | 2023 |
| Real-analytic diffeomorphisms with homogeneous spectrum and disjointness of convolutions S Banerjee, P Kunde arXiv preprint arXiv:1711.02537, 2017 | 3 | 2017 |
| Slow entropy for some Anosov-Katok diffeomorphisms S Banerjee, P Kunde, D Wei Discrete and Continuous Dynamical Systems 43 (1), 209-255, 2023 | 2 | 2023 |
| Real-analytic AbC Method on the Torus S Banerjee Pennsylvania State University, 2017 | 2 | 2017 |
| Ergodic and mixing quantum channels: From two-qubit to many-body quantum systems S Aravinda, S Banerjee, R Modak Physical Review A 110 (4), 042607, 2024 | 1 | 2024 |
| Non-standard real-analytic realizations of some rotations of the circle–CORRIGENDUM S Banerjee Ergodic Theory and Dynamical Systems 37 (5), 1387-1388, 2017 | 1 | 2017 |
| Weak mixing behavior for the projectivized derivative extension S Banerjee, D Khurana, P Kunde arXiv preprint arXiv:2412.21041, 2024 | | 2024 |
| A study on smooth activation functions K Biswas, AK Pandey, S Banerjee IIIT-Delhi, 2023 | | 2023 |
| Information and entropy in dynamical systems. An introduction S Banerjee, F Ledrappier | | 2012 |
Ashish Kumar PandeyAssistant Professor of Mathematics, Indraprastha Institute of Information Technology DelhiEmail verificata su iiitd.ac.in