Shuheng Liu

According to our database, Shuheng Liu authored at least 10 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Bounding entanglement dimensionality from the covariance matrix.

Shuheng Liu, Matteo Fadel, Qiongyi He, Marcus Huber, Giuseppe Vitagliano

Quantum, January, 2024

Gravitational Duals from Equations of State.

Yago Bea, Raúl Jiménez, David Mateos, Shuheng Liu, Pavlos Protopapas, Pedro Tarancón-Álvarez, Pablo Tejerina-Pérez

CoRR, 2024

Universal NER: A Gold-Standard Multilingual Named Entity Recognition Benchmark.

Stephen Mayhew, Terra Blevins, Shuheng Liu, Marek Suppa, Hila Gonen, Joseph Marvin Imperial, Börje Karlsson, Peiqin Lin, Nikola Ljubesic, Lester James V. Miranda, Barbara Plank, Arij Riabi, Yuval Pinter

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

2023

Universal NER: A Gold-Standard Multilingual Named Entity Recognition Benchmark.

Stephen Mayhew, Terra Blevins, Shuheng Liu, Marek Suppa, Hila Gonen, Joseph Marvin Imperial, Börje F. Karlsson, Peiqin Lin, Nikola Ljubesic, LJ Miranda, Barbara Plank, Arij Riabi, Yuval Pinter

CoRR, 2023

Multimodal N-of-1 trials: A Novel Personalized Healthcare Design.

Jingjing Fu, Shuheng Liu, Siqi Du, Siqiao Ruan, Xuliang Guo, Weiwei Pan, Abhishek Sharma, Stefan Konigorski

CoRR, 2023

Residual-based error bound for physics-informed neural networks.

Shuheng Liu, Xiyue Huang, Pavlos Protopapas

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Do CoNLL-2003 Named Entity Taggers Still Work Well in 2023?

Shuheng Liu, Alan Ritter

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

Evaluating Error Bound for Physics-Informed Neural Networks on Linear Dynamical Systems.

Shuheng Liu, Xiyue Huang, Pavlos Protopapas

CoRR, 2022

2020

NeuroDiffEq: A Python package for solving differential equations with neural networks.

Feiyu Chen, David Sondak, Pavlos Protopapas, Marios Mattheakis, Shuheng Liu, Devansh Agarwal, Marco Di Giovanni

J. Open Source Softw., 2020

2019

Classification of Canker on Small Datasets Using Improved Deep Convolutional Generative Adversarial Networks.

Min Zhang, Shuheng Liu, Fangyun Yang, Ji Liu

IEEE Access, 2019