195 citations · 458 across the 33 of their papers we have counts for
5 papers · 1 filter
Emulating Spatio-Temporal Realizations of Three-Dimensional Isotropic Turbulence via Deep Sequence Learning Models
Mohammadreza Momenifar, Enmao Diao, Vahid Tarokh +1
We use a data-driven approach to model a three-dimensional turbulent flow using cutting-edge Deep Learning techniques. The deep learning framework incorporates physical constraints…
Decentralized Multi-Target Cross-Domain Recommendation for Multi-Organization Collaborations
Enmao Diao, Vahid Tarokh, Jie Ding
Recommender Systems (RSs) are operated locally by different organizations in many realistic scenarios. If various organizations can fully share their data and perform computation i…
SemiFL: Semi-Supervised Federated Learning for Unlabeled Clients with Alternate Training
Enmao Diao, Jie Ding, Vahid Tarokh
Federated Learning allows the training of machine learning models by using the computation and private data resources of many distributed clients. Most existing results on Federate…
GAL: Gradient Assisted Learning for Decentralized Multi-Organization Collaborations
Enmao Diao, Jie Ding, Vahid Tarokh
Collaborations among multiple organizations, such as financial institutions, medical centers, and retail markets in decentralized settings are crucial to providing improved service…
Dimension Reduced Turbulent Flow Data From Deep Vector Quantizers
Mohammadreza Momenifar, Enmao Diao, Vahid Tarokh +1
Analyzing large-scale data from simulations of turbulent flows is memory intensive, requiring significant resources. This major challenge highlights the need for data compression t…