Personal information

China

Activities

Employment (1)

Shanghai Center for Brain Science and Brain-Inspired Technology: Shanghai, CN

2021-08-31 to present
Employment
Source: Self-asserted source
Xingyu Li

Education and qualifications (3)

University of California Santa Cruz: Santa Cruz, CA, US

2018-09-20 to 2020-06-30 | Master of Science in Computer Science (Computer Science)
Education
Source: Self-asserted source
Xingyu Li

University of Science and Technology of China: Hefei, Anhui, CN

2011-09-01 to 2017-06-20 | Doctor of Natural Science in Physics (Modern Physics)
Education
Source: Self-asserted source
Xingyu Li

Anhui Jianzhu University: Hefei, Anhui, CN

2007-09-01 to 2011-07-01 | Bachelor of Science (Applied Physics)
Education
Source: Self-asserted source
Xingyu Li

Works (18)

GeoDTR+: Toward Generic Cross-View Geolocalization via Geometric Disentanglement

IEEE Transactions on Pattern Analysis and Machine Intelligence
2024 | Journal article
Contributors: Xiaohan Zhang; Xingyu Li; Waqas Sultani; Chen Chen; Safwan Wshah
Source: check_circle
Crossref

Denoised Internal Models: A Brain-inspired Autoencoder Against Adversarial Attacks

Machine Intelligence Research
2022-10 | Journal article
Contributors: Kai-Yuan Liu; Xing-Yu Li; Yu-Rui Lai; Hang Su; Jia-Chen Wang; Chun-Xu Guo; Hong Xie; Ji-Song Guan; Yi Zhou
Source: check_circle
Crossref

Distorted-wave description of electron momentum spectroscopy for molecules: A demonstration for molecular oxygen

Physical Review A
2022-04-07 | Journal article
Contributors: Maomao Gong; Yuting Zhang; Xingyu Li; Song Bin Zhang; Xu Shan; Xiangjun Chen
Source: check_circle
Crossref

Research Replication Prediction Using Weakly Supervised Learning

Findings of the Association for Computational Linguistics: EMNLP 2020
2020-11 | Conference paper
Source: Self-asserted source
Xingyu Li

Learning with Instance-Dependent Label Noise: A Sample Sieve Approach

2020-10-05 | Preprint
Source: Self-asserted source
Xingyu Li

Sample Elicitation

2019-10-08 | Preprint
Source: Self-asserted source
Xingyu Li

Theoretical study of electron impact triple differential cross sections of N 2 O by a multicenter distorted-wave method

Journal of Physics B: Atomic, Molecular and Optical Physics
2018-05 | Journal article
Source: Self-asserted source
Xingyu Li

Two-center interference in electron-impact ionization of molecular hydrogen

Physical Review A
2018-02 | Journal article
Source: Self-asserted source
Xingyu Li

Theoretical study of (e, 2e) processes for valence orbitals of CH4 using a multicenter distorted-wave method

Physical Review A
2017-10 | Journal article
Source: Self-asserted source
Xingyu Li

Single-electron capture in 3-keV/u Ar8+-He collisions

Physical Review A
2017-04 | Journal article
Source: Self-asserted source
Xingyu Li

Calculation of (e, 2e) triple-differential cross sections of formic acid: An application of the multicenter distorted-wave method

Physical Review A
2017-01 | Journal article
Source: Self-asserted source
Xingyu Li

Spin-resolved electron capture cross sections for C5+ -H collisions

Journal of Physics B: Atomic, Molecular and Optical Physics
2015 | Journal article
Source: Self-asserted source
Xingyu Li

Three-body fragmentation dynamics of CO4+ 2 investigated by electron collision at impact energy of 500 eV

Physical Review A
2015-12 | Journal article
Source: Self-asserted source
Xingyu Li

Radiative association processes to specific rovibrational levels in low-energy Na+ +87Rb collisions

Physical Review A
2014-09 | Journal article
Source: Self-asserted source
Xingyu Li

Cross sections for electron capture and excitation in collisions of Liq+ (q=1, 2, 3) with atomic hydrogen

Physics of Plasmas
2014-06 | Journal article
Source: Self-asserted source
Xingyu Li

Multicenter distorted-wave method for fast-electron-impact single ionization of molecules

Physical Review A
2014-05 | Journal article
Source: Self-asserted source
Xingyu Li

DDDM: A Brain-Inspired Framework for Robust Classification

31st International Joint Conference on Artificial Intelligence
Conference paper
Source: Self-asserted source
Xingyu Li

SHAPE: An Unified Approach to Evaluate the Contribution and Cooperation of Individual Modalities

The 31st International Joint Conference on Artificial Intelligence
Conference paper
Source: Self-asserted source
Xingyu Li