Search Results for author: Qiang Ma

Found 16 papers, 6 papers with code

Dual Attention Model for Citation Recommendation with Analyses on Explainability of Attention Mechanisms and Qualitative Experiments

no code implementations CL (ACL) 2022 Yang Zhang, Qiang Ma

A neural network model is designed to maximize the similarity between the embedding of the three inputs (local context words, section headers, and structural contexts) and the target citation appearing in the context.

Citation Recommendation

Multi-Granularity Framework for Unsupervised Representation Learning of Time Series

no code implementations12 Dec 2023 Chengyang Ye, Qiang Ma

In practice, data confusion is a significant issue as it can considerably impact the effectiveness and accuracy of data analysis, machine learning models and decision-making processes.

Decision Making Representation Learning +2

Conditional Temporal Attention Networks for Neonatal Cortical Surface Reconstruction

1 code implementation21 Jul 2023 Qiang Ma, Liu Li, Vanessa Kyriakopoulou, Joseph Hajnal, Emma C. Robinson, Bernhard Kainz, Daniel Rueckert

The importance of each SVF, which is estimated by learned attention maps, is conditioned on the age of the neonates and varies with the time step of integration.

Surface Reconstruction

Stabilize, Decompose, and Denoise: Self-Supervised Fluoroscopy Denoising

no code implementations30 Aug 2022 Ruizhou Liu, Qiang Ma, Zhiwei Cheng, Yuanyuan Lyu, Jianji Wang, S. Kevin Zhou

Fluoroscopy is an imaging technique that uses X-ray to obtain a real-time 2D video of the interior of a 3D object, helping surgeons to observe pathological structures and tissue functions especially during intervention.

Denoising Optical Flow Estimation +1

CortexODE: Learning Cortical Surface Reconstruction by Neural ODEs

1 code implementation16 Feb 2022 Qiang Ma, Liu Li, Emma C. Robinson, Bernhard Kainz, Daniel Rueckert, Amir Alansary

Following the isosurface extraction step, two CortexODE models are trained to deform the initial surface to white matter and pial surfaces respectively.

Surface Reconstruction

Recommending Multiple Positive Citations for Manuscript via Content-Dependent Modeling and Multi-Positive Triplet

no code implementations25 Nov 2021 Yang Zhang, Qiang Ma

Third, we propose a dynamic context sampling strategy which captures the ``macro-scoped'' citing intents from a manuscript and empowers the citation embeddings to be content-dependent, which allow the algorithm to further improve the performances.

Citation Recommendation

Recommending POIs for Tourists by User Behavior Modeling and Pseudo-Rating

1 code implementation13 Oct 2021 Kun Yi, Ryu Yamagishi, Taishan Li, Zhengyang Bai, Qiang Ma

Our mechanism include two components: one is a probabilistic model that reveals the user behaviors in tourism; the other is a pseudo rating mechanism to handle the cold-start issue in POIs recommendations.

Fairness Recommendation Systems

PialNN: A Fast Deep Learning Framework for Cortical Pial Surface Reconstruction

1 code implementation6 Sep 2021 Qiang Ma, Emma C. Robinson, Bernhard Kainz, Daniel Rueckert, Amir Alansary

Traditional cortical surface reconstruction is time consuming and limited by the resolution of brain Magnetic Resonance Imaging (MRI).

Surface Reconstruction

Real-Time AutoML

no code implementations1 Jan 2021 Iddo Drori, Brandon Kates, Anant Kharkar, Lu Liu, Qiang Ma, Jonah Deykin, Nihar Sidhu, Madeleine Udell

We train a graph neural network in which each node represents a dataset to predict the best machine learning pipeline for a new test dataset.

AutoML BIG-bench Machine Learning +1

Dual Attention Model for Citation Recommendation

no code implementations COLING 2020 Yang Zhang, Qiang Ma

For example, they do not consider the section of the paper that the user is writing and for which they need to find a citation, the relatedness between the words in the local context (the text span that describes a citation), or the importance on each word from the local context.

Citation Recommendation

Citation Recommendations Considering Content and Structural Context Embedding

no code implementations8 Jan 2020 Yang Zhang, Qiang Ma

The number of academic papers being published is increasing exponentially in recent years, and recommending adequate citations to assist researchers in writing papers is a non-trivial task.

Combinatorial Optimization by Graph Pointer Networks and Hierarchical Reinforcement Learning

2 code implementations12 Nov 2019 Qiang Ma, Suwen Ge, Danyang He, Darshan Thaker, Iddo Drori

Furthermore, to approximate solutions to constrained combinatorial optimization problems such as the TSP with time windows, we train hierarchical GPNs (HGPNs) using RL, which learns a hierarchical policy to find an optimal city permutation under constraints.

Combinatorial Optimization Graph Embedding +4

Exploring Cellular Protein Localization Through Semantic Image Synthesis

no code implementations25 Sep 2019 Daniel Li, Qiang Ma, Andrew Liu, Justin Cheung, Dana Pe’er, Itsik Pe’er

Cell-cell interactions have an integral role in tumorigenesis as they are critical in governing immune responses.

Image Generation Management +1

Dual Graph Convolutional Networks for Graph-Based Semi-Supervised Classification

1 code implementation World Wide Web Conference 2018 Chengyi Zhuang, Qiang Ma

Accordingly, two convolutional neural networks are devised to embed the local-consistency-based and global-consistency-based knowledge, respectively.

Classification

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