5 citations · 6 across the 3 of their papers we have counts for
3 papers
Selecting Subsets of Source Data for Transfer Learning with Applications in Metal Additive Manufacturing
Yifan Tang, M. Rahmani Dehaghani, Pouyan Sajadi +1
Considering data insufficiency in metal additive manufacturing (AM), transfer learning (TL) has been adopted to extract knowledge from source domains (e.g., completed printings) to…
Real-Time 2D Temperature Field Prediction in Metal Additive Manufacturing Using Physics-Informed Neural Networks
Pouyan Sajadi, Mostafa Rahmani Dehaghani, Yifan Tang +1
Accurately predicting the temperature field in metal additive manufacturing (AM) processes is critical to preventing overheating, adjusting process parameters, and ensuring process…
Comparison of Transfer Learning based Additive Manufacturing Models via A Case Study
Yifan Tang, M. Rahmani Dehaghani, G. Gary Wang
Transfer learning (TL) based additive manufacturing (AM) modeling is an emerging field to reuse the data from historical products and mitigate the data insufficiency in modeling ne…