News

2 papers accepted to CVPR 2022. 1 paper accepted to ICCS 2022.

We are hiring research interns for 2022!

We release a tensor learning library for PyTorch users (TensorLyTorch). Check out the website to learn how this can help with your deep learning models. [website] [github]
Research Interests

Recurrent Neural Network (RNN), MuitiDimensional LSTM

MultiDimensional Sequence Learning, SpatioTemporal Learning

Predictive Learning, Fewshot Learning, Lifelong Learning
Selected Projects
 B Wu*, O Hennigh, J Kautz, S Choudhry, W Byeon*, “Physics Informed RNNDCT Networks for TimeDependent Partial Differential Equations”, ICCS 2022 (*) equal contributions
 NeurIPS’21 Workshop on ML and the Physical Science

J Su, W Byeon, F Huang, “Scalingup Diverse Orthogonal Convolutional Networks with a Paraunitary Framework”, arXiv, 2021
 J Su*, W Byeon*, F Huang, J Kautz, A Anandkumar, “Convolutional TensorTrain LSTM for Spatiotemporal Learning”, NeurIPS 2020 (*) equal contributions
 [Project page]
 ECCV’20 Tutorial on Accelerating Computer Vision with Mixed Precision.

W Byeon, Q Wang, R K Srivastava, P Koumoutsakos, “ContextVP: Fully ContextAware Video Prediction”, ECCV 2018 (oral)
 PR Vlachas, W Byeon, ZY Wan, TP Sapsis, P Koumoutsakos, “DataDriven Forecasting of HighDimensional Chaotic Systems with Long ShortTerm Memory Networks”, Proceedings of the Royal Society A: Mathematical, Physical & Engineering Sciences. 2018