507 citations · 2.3k across the 101 of their papers we have counts for
19 papers · 1 filter
SESNet: sequence-structure feature-integrated deep learning method for data-efficient protein engineering
Mingchen Li, Liqi Kang, Yi Xiong +4
Deep learning has been widely used for protein engineering. However, it is limited by the lack of sufficient experimental data to train an accurate model for predicting the functio…
Determination of U-spin breaking parameters with an amplitude analysis of the decay
BESIII Collaboration, M. Ablikim, M. N. Achasov +605
We present a study of the resonant structure of the decay , using quantum-correlated data produced at GeV. The data sampl…
Neural Coreference Resolution based on Reinforcement Learning
Yu Wang, Hongxia Jin
The target of a coreference resolution system is to cluster all mentions that refer to the same entity in a given context. All coreference resolution systems need to solve two subt…
First Direct Measurement of the Absolute Branching Fraction of
BESIII Collaboration, M. Ablikim, M. N. Achasov +591
The first direct measurement of the absolute branching fraction of is reported based on an annihilation sample of eve…
Detecting Objects with Context-Likelihood Graphs and Graph Refinement
Aritra Bhowmik, Yu Wang, Nora Baka +2
The goal of this paper is to detect objects by exploiting their interrelationships. Contrary to existing methods, which learn objects and relations separately, our key idea is to l…
SPE-Net: Boosting Point Cloud Analysis via Rotation Robustness Enhancement
Zhaofan Qiu, Yehao Li, Yu Wang +3
In this paper, we propose a novel deep architecture tailored for 3D point cloud applications, named as SPE-Net. The embedded ``Selective Position Encoding (SPE)'' procedure relies…