105 citations · 286 across the 26 of their papers we have counts for
22 papers
Search for the doubly Cabibbo-suppressed decays and
BESIII Collaboration, M. Ablikim, M. N. Achasov +774
We present the first search for the doubly Cabibbo-suppressed decays and using an collision data sample corresponding to an…
Variational Rectification Inference for Learning with Noisy Labels
Haoliang Sun, Qi Wei, Lei Feng +4
Label noise has been broadly observed in real-world datasets. To mitigate the negative impact of overfitting to label noise for deep models, effective strategies (\textit{e.g.}, re…
Observation of decay
M. Ablikim
Using a sample of events collected with the BESIII detector, the decay with subsequently decaying into $γπ^+…
Measurements of the absolute branching fractions of decays and test of the rule
BESIII Collaboration, M. Ablikim, M. N. Achasov +610
Based on a data set of events collected at the BESIII experiment, the absolute branching fractions of the three dominant decays are meas…
Search for the semileptonic decays and
BESIII Collaboration, M. Ablikim, M. N. Achasov +611
By analyzing 7.33\,fb of collision data collected at center-of-mass energies between 4.128 and 4.226 GeV with the BESIII detector, we search for the semileptonic de…
A coupled-channel analysis of the lineshape with BESIII data
BESIII Collaboration, M. Ablikim, M. N. Achasov +611
We perform a study of the lineshape using the data samples of , and collected with the BESIII detector. The…
Investigation of the rule and test of CP violation through the measurement of decay asymmetry parameters in decays
BESIII Collaboration, M. Ablikim, M. N. Achasov +615
Using events collected with the BESIII detector, numerous and decay asymmetry parameters are simultaneously determined from the process…
Measurement of the cross sections from 2.000 to 3.080 GeV
BESIII Collaboration, M. Ablikim, M. N. Achasov +615
Based on collision data collected at center-of-mass energies from 2.000 to 3.080 GeV by the BESIII detector at the BEPCII collider, a partial wave analysis is performe…
Observation of in the amplitude analysis of
BESIII Collaboration, M. Ablikim, M. N. Achasov +615
We perform for the first time an amplitude analysis of the decay and report the observation of the decay using 2.93 fb$^…
Measurement of the cross section of at center-of-mass energies between 3.510 and 4.843 GeV
BESIII Collaboration, M. Ablikim, M. N. Achasov +610
Using collision data corresponding to a total integrated luminosity of 12.9 collected with the BESIII detector at the BEPCII collider, the exclusive Born cross s…
Measurement of cross sections at center-of-mass energies from 3.508 to 4.951 GeV and search for the decay
BESIII Collaboration, M. Ablikim, M. N. Achasov +611
The cross sections of the process at center-of-mass energies from 3.508 to 4.951 GeV are measured with high precision using 26.1 fb data collected with th…
Measurement of the branching fractions of the singly Cabibbo-suppressed decays and
BESIII Collaboration, M. Ablikim, M. N. Achasov +618
Based on 4.5 $\mbox{fb$^{-1}$}$ collision data collected with BESIII detector at seven energy points between 4.600 and 4.699 GeV, the branching fractions for $Λ_{c}^{+…
Improving Generalization in Meta-Learning via Meta-Gradient Augmentation
Ren Wang, Haoliang Sun, Qi Wei +3
Meta-learning methods typically follow a two-loop framework, where each loop potentially suffers from notorious overfitting, hindering rapid adaptation and generalization to new ta…
MetaViewer: Towards A Unified Multi-View Representation
Ren Wang, Haoliang Sun, Yuling Ma +2
Existing multi-view representation learning methods typically follow a specific-to-uniform pipeline, extracting latent features from each view and then fusing or aligning them to o…
Fine-Grained Classification with Noisy Labels
Qi Wei, Lei Feng, Haoliang Sun +3
Learning with noisy labels (LNL) aims to ensure model generalization given a label-corrupted training set. In this work, we investigate a rarely studied scenario of LNL on fine-gra…
Self-Filtering: A Noise-Aware Sample Selection for Label Noise with Confidence Penalization
Qi Wei, Haoliang Sun, Xiankai Lu +1
Sample selection is an effective strategy to mitigate the effect of label noise in robust learning. Typical strategies commonly apply the small-loss criterion to identify clean sam…
Learning to Rectify for Robust Learning with Noisy Labels
Haoliang Sun, Chenhui Guo, Qi Wei +2
Label noise significantly degrades the generalization ability of deep models in applications. Effective strategies and approaches, \textit{e.g.} re-weighting, or loss correction, a…
Learning Transferable Parameters for Unsupervised Domain Adaptation
Zhongyi Han, Haoliang Sun, Yilong Yin
Unsupervised domain adaptation (UDA) enables a learning machine to adapt from a labeled source domain to an unlabeled domain under the distribution shift. Thanks to the strong repr…
Attentional Prototype Inference for Few-Shot Segmentation
Haoliang Sun, Xiankai Lu, Haochen Wang +4
This paper aims to address few-shot segmentation. While existing prototype-based methods have achieved considerable success, they suffer from uncertainty and ambiguity caused by li…
Search for the rare semi-leptonic decay
BESIII Collaboration, M. Ablikim, M. N. Achasov +503
Using events produced by the Beijing Electron Positron Collider (BEPCII) at a center-of-mass energy and collected with the BESIII…
Direct Estimation of Spinal Cobb Angles by Structured Multi-Output Regression
Haoliang Sun, Xiantong Zhen, Chris Bailey +3
The Cobb angle that quantitatively evaluates the spinal curvature plays an important role in the scoliosis diagnosis and treatment. Conventional measurement of these angles suffers…
DUAL-GLOW: Conditional Flow-Based Generative Model for Modality Transfer
Haoliang Sun, Ronak Mehta, Hao H. Zhou +4
Positron emission tomography (PET) imaging is an imaging modality for diagnosing a number of neurological diseases. In contrast to Magnetic Resonance Imaging (MRI), PET is costly a…