activity
20202022
most citedCross-Modal Virtual Sensing for Combustion Instability Monitoring

1 citations · 2 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG2022★ 1 cited

A Deep Learning Approach to Detect Lean Blowout in Combustion Systems

Tryambak Gangopadhyay, Somnath De, Qisai Liu +3

Lean combustion is environment friendly with low NOx emissions and also provides better fuel efficiency in a combustion system. However, approaching towards lean combustion can mak…

cs.LG2021★ 1 cited

Cross-Modal Virtual Sensing for Combustion Instability Monitoring

Tryambak Gangopadhyay, Vikram Ramanan, Satyanarayanan R Chakravarthy +1

In many cyber-physical systems, imaging can be an important but expensive or 'difficult to deploy' sensing modality. One such example is detecting combustion instability using flam…

cs.LG2021

3D Convolutional Selective Autoencoder For Instability Detection in Combustion Systems

Tryambak Gangopadhyay, Vikram Ramanan, Adedotun Akintayo +4

While analytical solutions of critical (phase) transitions in physical systems are abundant for simple nonlinear systems, such analysis remains intractable for real-life dynamical…

cs.LG2020

Spatiotemporal Attention for Multivariate Time Series Prediction and Interpretation

Tryambak Gangopadhyay, Sin Yong Tan, Zhanhong Jiang +2

Multivariate time series modeling and prediction problems are abundant in many machine learning application domains. Accurate interpretation of such prediction outcomes from a mach…

cs.LG2020

Crop Yield Prediction Integrating Genotype and Weather Variables Using Deep Learning

Johnathon Shook, Tryambak Gangopadhyay, Linjiang Wu +3

Accurate prediction of crop yield supported by scientific and domain-relevant insights, can help improve agricultural breeding, provide monitoring across diverse climatic condition…