activity
20212023
most citedSMU: smooth activation function for deep networks using smoothing maximum technique

2 citations · 5 across the 9 of their papers we have counts for

collaborators

9 papers

math.AP2023★ 1 cited

Transverse spectral Instabilities in rotation-modified Kadomtsev-Petviashvili equation and related models

Bhavna, Ashish Kumar Pandey, Anastassiya Semenova

The rotation modified Kadomtsev Petviashvili equation which is also known as the Kadomtsev Petviashvili Ostrovsky equation, describes the gradual wave field diffusion in the transv…

math.AP2023

Modulational Instability in the Ostrovsky Equation and Related Models

Bhavna, Mathew A. Johnson, Ashish Kumar Pandey

We study the modulational instability of small-amplitude periodic traveling wave solutions in a dispersion generalized Ostrovsky equation. Specifically, we investigate the invertib…

physics.ao-ph2022★ 1 cited

Forecasting formation of a Tropical Cyclone Using Reanalysis Data

Sandeep Kumar, Koushik Biswas, Ashish Kumar Pandey

The tropical cyclone formation process is one of the most complex natural phenomena which is governed by various atmospheric, oceanographic, and geographic factors that varies with…

cs.LG2021★ 2 cited

SMU: smooth activation function for deep networks using smoothing maximum technique

Koushik Biswas, Sandeep Kumar, Shilpak Banerjee +1

Deep learning researchers have a keen interest in proposing two new novel activation functions which can boost network performance. A good choice of activation function can have si…

cs.LG2021

SAU: Smooth activation function using convolution with approximate identities

Koushik Biswas, Sandeep Kumar, Shilpak Banerjee +1

Well-known activation functions like ReLU or Leaky ReLU are non-differentiable at the origin. Over the years, many smooth approximations of ReLU have been proposed using various sm…

cs.NE2021

ErfAct and Pserf: Non-monotonic Smooth Trainable Activation Functions

Koushik Biswas, Sandeep Kumar, Shilpak Banerjee +1

An activation function is a crucial component of a neural network that introduces non-linearity in the network. The state-of-the-art performance of a neural network depends also on…

physics.ao-ph2021

Tropical cyclone intensity estimations over the Indian ocean using Machine Learning

Koushik Biswas, Sandeep Kumar, Ashish Kumar Pandey

Tropical cyclones are one of the most powerful and destructive natural phenomena on earth. Tropical storms and heavy rains can cause floods, which lead to human lives and economic…

cs.LG2021

Intensity Prediction of Tropical Cyclones using Long Short-Term Memory Network

Koushik Biswas, Sandeep Kumar, Ashish Kumar Pandey

Tropical cyclones can be of varied intensity and cause a huge loss of lives and property if the intensity is high enough. Therefore, the prediction of the intensity of tropical cyc…

cs.NE2021★ 1 cited

Orthogonal-Padé Activation Functions: Trainable Activation functions for smooth and faster convergence in deep networks

Koushik Biswas, Shilpak Banerjee, Ashish Kumar Pandey

We have proposed orthogonal-Padé activation functions, which are trainable activation functions and show that they have faster learning capability and improves the accuracy in stan…