| Big bird: Transformers for longer sequences M Zaheer, G Guruganesh, KA Dubey, J Ainslie, C Alberti, S Ontanon, ... Advances in Neural Information Processing Systems 33, 17283-17297, 2020 | 471 | 2020 |
| ETC: Encoding long and structured inputs in transformers J Ainslie, S Ontanon, C Alberti, V Cvicek, Z Fisher, P Pham, A Ravula, ... arXiv preprint arXiv:2004.08483, 2020 | 111 | 2020 |
| Strongly interacting quantum gases in one-dimensional traps L Yang, L Guan, H Pu Physical Review A 91 (4), 043634, 2015 | 67 | 2015 |
| Bose-Fermi mapping and a multibranch spin-chain model for strongly interacting quantum gases in one dimension: Dynamics and collective excitations L Yang, H Pu Physical Review A 94 (3), 033614, 2016 | 25 | 2016 |
| Learning to extract attribute value from product via question answering: A multi-task approach Q Wang, L Yang, B Kanagal, S Sanghai, D Sivakumar, B Shu, Z Yu, ... Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 17 | 2020 |
| Deep learning-enhanced variational Monte Carlo method for quantum many-body physics L Yang, Z Leng, G Yu, A Patel, WJ Hu, H Pu Physical Review Research 2 (1), 012039, 2020 | 13 | 2020 |
| One-body density matrix and momentum distribution of strongly interacting one-dimensional spinor quantum gases L Yang, H Pu Physical Review A 95 (5), 051602, 2017 | 10 | 2017 |
| Big bird: Transformers for longer sequences. arXiv 2020 M Zaheer, G Guruganesh, A Dubey, J Ainslie, C Alberti, S Ontanon, ... arXiv preprint arXiv:2007.14062, 0 | 5 | |
| Scalable variational Monte Carlo with graph neural ansatz L Yang, W Hu, L Li arXiv preprint arXiv:2011.12453, 2020 | 3 | 2020 |
| MAVE: A Product Dataset for Multi-source Attribute Value Extraction L Yang, Q Wang, Z Yu, A Kulkarni, S Sanghai, B Shu, J Elsas, B Kanagal Proceedings of the Fifteenth ACM International Conference on Web Search and …, 2022 | 2 | 2022 |
| Dynamical Fermionization in One-Dimensional Spinor Quantum Gases SS Alam, T Skaras, L Yang, H Pu Physical Review Letters 127 (2), 023002, 2021 | 1 | 2021 |
| Dynamical Fermionization and Scaling Behaviour for a Strongly Repulsive Spinor Gas after Quench SS Alam, T Skaras, L Yang, H Pu Bulletin of the American Physical Society 65, 2020 | | 2020 |
| Deep Convolutional Neural Networks for Quantum 1D Spin Chains SS Alam, L Yang, W Hu, Y Ju, H Pu, A Patel APS Division of Atomic, Molecular and Optical Physics Meeting Abstracts 2020 …, 2020 | | 2020 |
| Predicting Relapse in Patients With Triple Negative Breast Cancer (TNBC) Using a Deep-Learning Approach G Yu, X Li, TF He, T Gruosso, D Zuo, M Souleimanova, VM Ramos, ... Frontiers in physiology, 1213, 2020 | | 2020 |
| Exploring Deep Convolutional Network Architectures for Quantum 1D Spin Chains SS Alam, L Yang, Y Ju, W Hu, H Pu, A Patel APS Division of Atomic, Molecular and Optical Physics Meeting Abstracts 2020 …, 2020 | | 2020 |
| Dynamical Fermionization, Tan Contact, and Scalings for a Strongly Interacting Gas after quench SS Alam, T Skaras, L Yang, H Pu APS Division of Atomic, Molecular and Optical Physics Meeting Abstracts 2019 …, 2019 | | 2019 |
| Strongly Interacting One-Dimensional Spinor Quantum Gases L Yang Rice University, 2019 | | 2019 |
| Momentum distribution and Tan contact matrix for 1D spinor quantum gas in strong interacting limit SS Alam, L Yang, H Pu APS Division of Atomic, Molecular and Optical Physics Meeting Abstracts 2018 …, 2018 | | 2018 |
| One Body Density Matrix for Strongly Interacting Spinor Gases in 1D L Yang, H Pu APS March Meeting Abstracts 2017, P19. 003, 2017 | | 2017 |
| Multi-Branch Spin Chain Models for Strongly interacting Spinor Fermi and Bose gases in One-Dimension L Yang, H Pu APS March Meeting Abstracts 2016, S50. 002, 2016 | | 2016 |
Qifan WangResearch Scientist, Meta AIVerified email at fb.com
