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ORCIDYunchao Liu
This is just a disambiguation page, and is not intended to be the bibliography of an actual person. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.
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Journal Articles
- 2024
[j3]Grace Zhang, Xiaohan Kuang, Yuhao Zhang, Yunchao Liu, Zhaoqian Su, Tom Zhang, Yinghao Wu
:
Machine-learning-based structural analysis of interactions between antibodies and antigens. Biosyst. 243: 105264 (2024)- 2022
- [j2]Mingyue Cui, Yuzhang Zhu, Yechang Liu, Yunchao Liu, Gang Chen, Kai Huang:
Dense Depth-Map Estimation Based on Fusion of Event Camera and Sparse LiDAR. IEEE Trans. Instrum. Meas. 71: 1-11 (2022) - 2019
- [j1]Qi Zhao, Yunchao Liu, Xiao Yuan, Eric Chitambar, Andreas J. Winter:
One-Shot Coherence Distillation: Towards Completing the Picture. IEEE Trans. Inf. Theory 65(10): 6441-6453 (2019)
Conference and Workshop Papers
- 2024
- [c11]Jeongwan Haah, Yunchao Liu, Xinyu Tan:
Efficient Approximate Unitary Designs from Random Pauli Rotations. FOCS 2024: 463-475 - [c10]Thiago Bergamaschi, Chi-Fang Chen, Yunchao Liu:
Quantum Computational Advantage with Constant-Temperature Gibbs Sampling. FOCS 2024: 1063-1085 - [c9]Yu Wang, Tong Zhao, Yuying Zhao, Yunchao Liu, Xueqi Cheng, Neil Shah, Tyler Derr:
A Topological Perspective on Demystifying GNN-Based Link Prediction Performance. ICLR 2024 - [c8]Hsin-Yuan Huang, Yunchao Liu, Michael Broughton, Isaac Kim, Anurag Anshu, Zeph Landau, Jarrod R. McClean:
Learning Shallow Quantum Circuits. STOC 2024: 1343-1351 - 2023
- [c7]Yunchao Liu, Yu Wang, Oanh Vu, Rocco Moretti, Bobby Bodenheimer, Jens Meiler, Tyler Derr:
Interpretable Chirality-Aware Graph Neural Network for Quantitative Structure Activity Relationship Modeling in Drug Discovery. AAAI 2023: 14356-14364 - [c6]Yunchao Liu, Jie Gong:
DRL-Based UAV Trajectory Planning for AoS and Energy Consumption Minimization Assisted by AoI. GLOBECOM 2023: 1866-1871 - [c5]Dorit Aharonov, Xun Gao, Zeph Landau, Yunchao Liu, Umesh V. Vazirani:
A Polynomial-Time Classical Algorithm for Noisy Random Circuit Sampling. STOC 2023: 945-957 - 2022
- [c4]Anurag Anshu, Zeph Landau, Yunchao Liu:
Distributed Quantum inner product estimation. STOC 2022: 44-51 - 2021
- [c3]Adam Bouland, Bill Fefferman, Zeph Landau, Yunchao Liu:
Noise and the Frontier of Quantum Supremacy. FOCS 2021: 1308-1317 - 2020
- [c2]Yunchao Liu, Rocco Moretti, Bobby Bodenheimer, Jens Meiler:
Foldit Drug Design Game Usability Study: Comparison of Citizen and Expert Scientists. MIG 2020: 20:1-20:19 - 2019
- [c1]Yunchao Liu, Zheng Wu, Daniel Ritchie, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu:
Learning to Describe Scenes with Programs. ICLR (Poster) 2019
Informal and Other Publications
- 2024
- [i10]Hsin-Yuan Huang, Yunchao Liu, Michael Broughton, Isaac Kim, Anurag Anshu, Zeph Landau, Jarrod R. McClean:
Learning shallow quantum circuits. CoRR abs/2401.10095 (2024) - [i9]Jeongwan Haah, Yunchao Liu, Xinyu Tan:
Efficient approximate unitary designs from random Pauli rotations. CoRR abs/2402.05239 (2024) - [i8]Chi-Fang Chen, Jeongwan Haah, Jonas Haferkamp, Yunchao Liu, Tony Metger, Xinyu Tan:
Incompressibility and spectral gaps of random circuits. CoRR abs/2406.07478 (2024) - [i7]Xueqi Cheng, Yu Wang, Yunchao Liu, Yuying Zhao, Charu C. Aggarwal, Tyler Derr:
Edge Classification on Graphs: New Directions in Topological Imbalance. CoRR abs/2406.11685 (2024) - [i6]Zeph Landau, Yunchao Liu:
Learning quantum states prepared by shallow circuits in polynomial time. CoRR abs/2410.23618 (2024) - 2023
- [i5]Yuying Zhao, Yu Wang, Yunchao Liu, Xueqi Cheng, Charu C. Aggarwal, Tyler Derr:
Fairness and Diversity in Recommender Systems: A Survey. CoRR abs/2307.04644 (2023) - [i4]Yu Wang, Tong Zhao, Yuying Zhao, Yunchao Liu, Xueqi Cheng, Neil Shah, Tyler Derr:
A Topological Perspective on Demystifying GNN-Based Link Prediction Performance. CoRR abs/2310.04612 (2023) - 2021
- [i3]Adam Bouland, Bill Fefferman, Zeph Landau, Yunchao Liu:
Noise and the frontier of quantum supremacy. CoRR abs/2102.01738 (2021) - 2020
- [i2]Yunchao Liu, Srinivasan Arunachalam, Kristan Temme:
A rigorous and robust quantum speed-up in supervised machine learning. CoRR abs/2010.02174 (2020) - 2018
- [i1]Qi Zhao, Yunchao Liu, Xiao Yuan, Eric Chitambar, Andreas J. Winter:
One-Shot Coherence Distillation: The Full Story. CoRR abs/1808.01885 (2018)
Coauthor Index
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