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Li Yang
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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
6092020
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
1072020
Strongly interacting quantum gases in one-dimensional traps
L Yang, L Guan, H Pu
Physical Review A 91 (4), 043634, 2015
692015
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
282020
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
262020
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
262016
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
112017
Scalable variational Monte Carlo with graph neural ansatz
L Yang, W Hu, L Li
arXiv preprint arXiv:2011.12453, 2020
72020
Dynamical Fermionization in One-Dimensional Spinor Quantum Gases
SS Alam, T Skaras, L Yang, H Pu
Physical Review Letters 127 (2), 023002, 2021
62021
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
6
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
32022
Generalized Bose-Fermi mapping and strong coupling ansatz wavefunction for one dimensional strongly interacting spinor quantum gases
L Yang, SS Alam, H Pu
arXiv preprint arXiv:2208.01199, 2022
2022
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 11, 511071, 2020
2020
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
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
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