Piyush M. Mehta

According to our database, Piyush M. Mehta authored at least 14 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Neural-Based Compression Scheme for Solar Image Data.

Ali Zafari, Atefeh Khoshkhahtinat, Jeremy A. Grajeda, Piyush M. Mehta, Nasser M. Nasrabadi, Laura E. Boucheron, Barbara J. Thompson, Michael S. F. Kirk, Daniel Da Silva

IEEE Trans. Aerosp. Electron. Syst., February, 2024

Laplacian-guided Entropy Model in Neural Codec with Blur-dissipated Synthesis.

Atefeh Khoshkhahtinat, Ali Zafari, Piyush M. Mehta, Nasser M. Nasrabadi

CoRR, 2024

2023

Probabilistic Solar Proxy Forecasting with Neural Network Ensembles.

Joshua D. Daniell, Piyush M. Mehta

CoRR, 2023

Multi-Spectral Entropy Constrained Neural Compression of Solar Imagery.

Ali Zafari, Atefeh Khoshkhahtinat, Piyush M. Mehta, Nasser M. Nasrabadi, Barbara J. Thompson, Michael S. F. Kirk, Daniel Da Silva

Proceedings of the International Conference on Machine Learning and Applications, 2023

Context-Aware Neural Video Compression on Solar Dynamics Observatory.

Atefeh Khoshkhahtinat, Ali Zafari, Piyush M. Mehta, Nasser M. Nasrabadi, Barbara J. Thompson, Michael S. F. Kirk, Daniel Da Silva

Proceedings of the International Conference on Machine Learning and Applications, 2023

Multi-Context Dual Hyper-Prior Neural Image Compression.

Atefeh Khoshkhahtinat, Ali Zafari, Piyush M. Mehta, Mohammad Akyash, Hossein Kashiani, Nasser M. Nasrabadi

Proceedings of the International Conference on Machine Learning and Applications, 2023

Frequency Disentangled Features in Neural Image Compression.

Ali Zafari, Atefeh Khoshkhahtinat, Piyush M. Mehta, Mohammad Saeed Ebrahimi Saadabadi, Mohammad Akyash, Nasser M. Nasrabadi

Proceedings of the IEEE International Conference on Image Processing, 2023

2022

Reduced Order Probabilistic Emulation for Physics-Based Thermosphere Models.

Richard J. Licata, Piyush M. Mehta

CoRR, 2022

Calibrated and Enhanced NRLMSIS 2.0 Model with Uncertainty Quantification.

Richard J. Licata, Piyush M. Mehta, Daniel R. Weimer, W. Kent Tobiska, Jean Yoshii

CoRR, 2022

Science through Machine Learning: Quantification of Poststorm Thermospheric Cooling.

Richard J. Licata, Piyush M. Mehta, Daniel R. Weimer, Douglas P. Drob, W. Kent Tobiska, Jean Yoshii

CoRR, 2022

Uncertainty Quantification Techniques for Space Weather Modeling: Thermospheric Density Application.

Richard J. Licata, Piyush M. Mehta

CoRR, 2022

Attention-Based Generative Neural Image Compression on Solar Dynamics Observatory.

Ali Zafari, Atefeh Khoshkhahtinat, Piyush M. Mehta, Nasser M. Nasrabadi, Barbara J. Thompson, Daniel Da Silva, Michael S. F. Kirk

Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022

2021

Machine-Learned HASDM Model with Uncertainty Quantification.

Richard J. Licata, Piyush M. Mehta, W. Kent Tobiska, Snehalata V. Huzurbazar

CoRR, 2021

2018

Data-driven framework for real-time thermospheric density estimation.

Piyush M. Mehta, Richard Linares

CoRR, 2018