Search Results for author: Di Zhou

Found 7 papers, 1 papers with code

Topological Invariant and Anomalous Edge States of Strongly Nonlinear Systems

no code implementations28 Dec 2020 Di Zhou

In this work, we identify the proper definition of Berry phase for nonlinear bulk modes and characterize topological phases in one-dimensional (1D) generalized nonlinear Schr\"{o}dinger equations in the strongly nonlinear regime.

Quantization Disordered Systems and Neural Networks Optics

Novel Strongly Correlated Europium Superhydrides

no code implementations10 Dec 2020 Dmitrii V. Semenok, Di Zhou, Alexander G. Kvashnin, Xiaoli Huang, Michele Galasso, Ivan A. Kruglov, Anna G. Ivanova, Alexander G. Gavrilyuk, Wuhao Chen, Nikolay V. Tkachenko, Alexander I. Boldyrev, Ivan Troyan, Artem R. Oganov, Tian Cui

We conducted a joint experimental-theoretical investigation of the high-pressure chemistry of europium polyhydrides at pressures of 86-130 GPa.

Strongly Correlated Electrons Materials Science

PPKE: Knowledge Representation Learning by Path-based Pre-training

no code implementations7 Dec 2020 Bin He, Di Zhou, Jing Xie, Jinghui Xiao, Xin Jiang, Qun Liu

Entities may have complex interactions in a knowledge graph (KG), such as multi-step relationships, which can be viewed as graph contextual information of the entities.

Link Prediction Representation Learning

Integrating Graph Contextualized Knowledge into Pre-trained Language Models

no code implementations30 Nov 2019 Bin He, Di Zhou, Jinghui Xiao, Xin Jiang, Qun Liu, Nicholas Jing Yuan, Tong Xu

Complex node interactions are common in knowledge graphs, and these interactions also contain rich knowledge information.

Knowledge Graphs Representation Learning

Neural Relation Classification with Text Descriptions

no code implementations COLING 2018 Feiliang Ren, Di Zhou, Zhihui Liu, Yongcheng Li, Rongsheng Zhao, Yongkang Liu, Xiaobo Liang

State-of-the-art methods usually concentrate on building deep neural networks based classification models on the training data in which the relations of the labeled entity pairs are given.

General Classification Relation Classification

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