120 citations · 208 across the 23 of their papers we have counts for
23 papers
No Imputation Needed: A Switch Approach to Irregularly Sampled Time Series
Rohit Agarwal, Aman Sinha, Ayan Vishwakarma +5
Modeling irregularly-sampled time series (ISTS) is challenging because of missing values. Most existing methods focus on handling ISTS by converting irregularly sampled data into r…
Taxonomy of hybridly polarized Stokes vortex beams
Gauri Arora, Ankit Butola, Ruchi Rajput +5
Structured beams carrying topological defects, namely phase and Stokes singularities, have gained extensive interest in numerous areas of optics. The non-separable spin and orbital…
MiShape: 3D Shape Modelling of Mitochondria in Microscopy
Abhinanda R. Punnakkal, Suyog S Jadhav, Alexander Horsch +2
Fluorescence microscopy is a quintessential tool for observing cells and understanding the underlying mechanisms of life-sustaining processes of all living organisms. The problem o…
Physics-guided Loss Functions Improve Deep Learning Performance in Inverse Scattering
Zicheng Liu, Mayank Roy, Dilip K. Prasad +1
Solving electromagnetic inverse scattering problems (ISPs) is challenging due to the intrinsic nonlinearity, ill-posedness, and expensive computational cost. Recently, deep neural…
Artefact removal in ground truth and noise model deficient sub-cellular nanoscopy images using auto-encoder deep learning
Suyog Jadhav, Sebastian Acuña, Krishna Agarwal +1
Image denoising or artefact removal using deep learning is possible in the availability of supervised training dataset acquired in real experiments or synthesized using known noise…
Simulation-supervised deep learning for analysing organelles states and behaviour in living cells
Arif Ahmed Sekh, Ida S. Opstad, Rohit Agarwal +5
In many real-world scientific problems, generating ground truth (GT) for supervised learning is almost impossible. The causes include limitations imposed by scientific instrument,…