Search Results for author: Meng Liu

Found 41 papers, 25 papers with code

Cross-modal Audio-visual Co-learning for Text-independent Speaker Verification

1 code implementation22 Feb 2023 Meng Liu, Kong Aik Lee, Longbiao Wang, Hanyi Zhang, Chang Zeng, Jianwu Dang

Visual speech (i. e., lip motion) is highly related to auditory speech due to the co-occurrence and synchronization in speech production.

Text-Independent Speaker Verification

Self-Supervised Temporal Graph learning with Temporal and Structural Intensity Alignment

no code implementations15 Feb 2023 Meng Liu, Ke Liang, Bin Xiao, Sihang Zhou, Wenxuan Tu, Yue Liu, Xihong Yang, Xinwang Liu

To solve this issue, by extracting both temporal and structural information to learn more informative node representations, we propose a self-supervised method termed S2T for temporal graph learning.

Graph Learning

A Survey of Knowledge Graph Reasoning on Graph Types: Static, Dynamic, and Multimodal

1 code implementation12 Dec 2022 Ke Liang, Lingyuan Meng, Meng Liu, Yue Liu, Wenxuan Tu, Siwei Wang, Sihang Zhou, Xinwang Liu, Fuchun Sun

The early works in this domain mainly focus on static KGR and tend to directly apply general knowledge graph embedding models to the reasoning task.

General Knowledge Knowledge Graph Embedding +3

COVID-19 Activity Risk Calculator as a Gamified Public Health Intervention Tool

1 code implementation5 Dec 2022 Shreyasvi Natraj, Malhar Bhide, Nathan Yap, Meng Liu, Agrima Seth, Jonathan Berman, Christin Glorioso

Public health intervention techniques have been highly significant in reducing the negative impact of several epidemics and pandemics.

Coordinating Cross-modal Distillation for Molecular Property Prediction

no code implementations30 Nov 2022 Hao Zhang, Nan Zhang, Ruixin Zhang, Lei Shen, Yingyi Zhang, Meng Liu

The existing graph methods have demonstrated that 3D geometric information is significant for better performance in MPP.

Graph Regression Graph Representation Learning +3

DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding

no code implementations21 Nov 2022 Haitao Lin, Yufei Huang, Meng Liu, Xuanjing Li, Shuiwang Ji, Stan Z. Li

Previous works usually generate atoms in an auto-regressive way, where element types and 3D coordinates of atoms are generated one by one.

Drug Discovery

FedVMR: A New Federated Learning method for Video Moment Retrieval

no code implementations28 Oct 2022 Yan Wang, Xin Luo, Zhen-Duo Chen, Peng-Fei Zhang, Meng Liu, Xin-Shun Xu

As the first that is explored in VMR field, the new task is defined as video moment retrieval with distributed data.

Federated Learning Moment Retrieval +1

Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models

1 code implementation11 Oct 2022 Meng Liu, Haoran Liu, Shuiwang Ji

the discrete data space to approximately construct the provably optimal proposal distribution, which is subsequently used by importance sampling to efficiently estimate the original ratio matching objective.

Graph Generation

Spoofing-Aware Attention based ASV Back-end with Multiple Enrollment Utterances and a Sampling Strategy for the SASV Challenge 2022

no code implementations1 Sep 2022 Chang Zeng, Lin Zhang, Meng Liu, Junichi Yamagishi

Current state-of-the-art automatic speaker verification (ASV) systems are vulnerable to presentation attacks, and several countermeasures (CMs), which distinguish bona fide trials from spoofing ones, have been explored to protect ASV.

Speaker Verification

Topological structure of complex predictions

1 code implementation28 Jul 2022 Meng Liu, Tamal K. Dey, David F. Gleich

Complex prediction models such as deep learning are the output from fitting machine learning, neural networks, or AI models to a set of training data.

Image Classification Topological Data Analysis

GraphFM: Improving Large-Scale GNN Training via Feature Momentum

1 code implementation14 Jun 2022 Haiyang Yu, Limei Wang, Bokun Wang, Meng Liu, Tianbao Yang, Shuiwang Ji

GraphFM-IB applies FM to in-batch sampled data, while GraphFM-OB applies FM to out-of-batch data that are 1-hop neighborhood of in-batch data.

Node Classification

Your Neighbors Are Communicating: Towards Powerful and Scalable Graph Neural Networks

no code implementations4 Jun 2022 Meng Liu, Haiyang Yu, Shuiwang Ji

Message passing graph neural networks (GNNs) are known to have their expressiveness upper-bounded by 1-dimensional Weisfeiler-Lehman (1-WL) algorithm.

Generating 3D Molecules for Target Protein Binding

1 code implementation19 Apr 2022 Meng Liu, Youzhi Luo, Kanji Uchino, Koji Maruhashi, Shuiwang Ji

Second, to preserve the desirable equivariance property, we select a local reference atom according to the designed auxiliary classifiers and then construct a local spherical coordinate system.

Drug Discovery

Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences

1 code implementation7 Feb 2022 Meng Liu, Shuiwang Ji

Therefore, our Neighbor2Seq naturally endows GNNs with the efficiency and advantages of deep learning operations on grid-like data by precomputing the Neighbor2Seq transformations.

Inductive Representation Learning in Temporal Networks via Mining Neighborhood and Community Influences

1 code implementation1 Oct 2021 Meng Liu, Yong liu

Therefore, we propose a new inductive network representation learning method called MNCI by mining neighborhood and community influences in temporal networks.

Link Prediction Node Classification +1

GraphEBM: Towards Permutation Invariant and Multi-Objective Molecular Graph Generation

no code implementations29 Sep 2021 Meng Liu, Keqiang Yan, Bora Oztekin, Shuiwang Ji

In this work, we propose GraphEBM, a molecular graph generation method via energy-based models (EBMs), as an exploratory work to perform permutation invariant and multi-objective molecule generation.

Drug Discovery Graph Generation +1

Gradient-Guided Importance Sampling for Learning Discrete Energy-Based Models

1 code implementation29 Sep 2021 Meng Liu, Haoran Liu, Shuiwang Ji

In this study, we propose ratio matching with gradient-guided importance sampling (RMwGGIS) to alleviate the above limitations.

Graph Generation

A Novel Patch Convolutional Neural Network for View-based 3D Model Retrieval

no code implementations25 Sep 2021 Zan Gao, Yuxiang Shao, Weili Guan, Meng Liu, Zhiyong Cheng, ShengYong Chen

Thus, we tackle this problem from the perspective of exploiting the relationships between patch features to capture long-range associations among multi-view images.


Multigranular Visual-Semantic Embedding for Cloth-Changing Person Re-identification

no code implementations10 Aug 2021 Zan Gao, Hongwei Wei, Weili Guan, Weizhi Nie, Meng Liu, Meng Wang

To solve these issues, in this work, a novel multigranular visual-semantic embedding algorithm (MVSE) is proposed for cloth-changing person ReID, where visual semantic information and human attributes are embedded into the network, and the generalized features of human appearance can be well learned to effectively solve the problem of clothing changes.

Person Re-Identification

Dynamic Modality Interaction Modeling for Image-Text Retrieval

1 code implementation ACM Special Interest Group on Information Retrieval 2021 Leigang Qu, Meng Liu, Jianlong Wu, Zan Gao, Liqiang Nie

To address these issues, we develop a novel modality interaction modeling network based upon the routing mechanism, which is the first unified and dynamic multimodal interaction framework towards image-text retrieval.

Cross-Modal Retrieval Information Retrieval +2

Multi-Modal Relational Graph for Cross-Modal Video Moment Retrieval

no code implementations CVPR 2021 Yawen Zeng, Da Cao, Xiaochi Wei, Meng Liu, Zhou Zhao, Zheng Qin

Toward this end, we contribute a multi-modal relational graph to capture the interactions among objects from the visual and textual content to identify the differences among similar video moment candidates.

Cross-Modal Retrieval Graph Matching +2

Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks

1 code implementation NeurIPS Workshop AI4Scien 2021 Meng Liu, Cong Fu, Xuan Zhang, Limei Wang, Yaochen Xie, Hao Yuan, Youzhi Luo, Zhao Xu, Shenglong Xu, Shuiwang Ji

We employ our methods to participate in the 2021 KDD Cup on OGB Large-Scale Challenge (OGB-LSC), which aims to predict the HOMO-LUMO energy gap of molecules.

Molecular Property Prediction

Exploring Deep Learning for Joint Audio-Visual Lip Biometrics

1 code implementation17 Apr 2021 Meng Liu, Longbiao Wang, Kong Aik Lee, Hanyi Zhang, Chang Zeng, Jianwu Dang

Audio-visual (AV) lip biometrics is a promising authentication technique that leverages the benefits of both the audio and visual modalities in speech communication.

Speaker Recognition

DIG: A Turnkey Library for Diving into Graph Deep Learning Research

1 code implementation23 Mar 2021 Meng Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Hao Yuan, Shurui Gui, Haiyang Yu, Zhao Xu, Jingtun Zhang, Yi Liu, Keqiang Yan, Haoran Liu, Cong Fu, Bora Oztekin, Xuan Zhang, Shuiwang Ji

Although there exist several libraries for deep learning on graphs, they are aiming at implementing basic operations for graph deep learning.

Benchmarking Graph Generation +1

Spherical Message Passing for 3D Graph Networks

1 code implementation ICLR 2022 Yi Liu, Limei Wang, Meng Liu, Xuan Zhang, Bora Oztekin, Shuiwang Ji

Based on such observations, we propose the spherical message passing (SMP) as a novel and powerful scheme for 3D molecular learning.

Representation Learning

GraphEBM: Molecular Graph Generation with Energy-Based Models

1 code implementation ICLR Workshop EBM 2021 Meng Liu, Keqiang Yan, Bora Oztekin, Shuiwang Ji

We note that most existing approaches for molecular graph generation fail to guarantee the intrinsic property of permutation invariance, resulting in unexpected bias in generative models.

Graph Generation Molecular Graph Generation

Advanced Graph and Sequence Neural Networks for Molecular Property Prediction and Drug Discovery

1 code implementation2 Dec 2020 Zhengyang Wang, Meng Liu, Youzhi Luo, Zhao Xu, Yaochen Xie, Limei Wang, Lei Cai, Qi Qi, Zhuoning Yuan, Tianbao Yang, Shuiwang Ji

Here we develop a suite of comprehensive machine learning methods and tools spanning different computational models, molecular representations, and loss functions for molecular property prediction and drug discovery.

BIG-bench Machine Learning Drug Discovery +1

The Diversified Ensemble Neural Network

no code implementations NeurIPS 2020 Shaofeng Zhang, Meng Liu, Junchi Yan

Ensemble is a general way of improving the accuracy and stability of learning models, especially for the generalization ability on small datasets.

Frame-wise Cross-modal Matching for Video Moment Retrieval

1 code implementation22 Sep 2020 Haoyu Tang, Jihua Zhu, Meng Liu, Member, IEEE, Zan Gao, Zhiyong Cheng

Another contribution is that we propose an additional predictor to utilize the internal frames in the model training to improve the localization accuracy.

Boundary Detection Moment Retrieval +1

Towards Deeper Graph Neural Networks

3 code implementations18 Jul 2020 Meng Liu, Hongyang Gao, Shuiwang Ji

Based on our theoretical and empirical analysis, we propose Deep Adaptive Graph Neural Network (DAGNN) to adaptively incorporate information from large receptive fields.

Graph Representation Learning Node Classification +1

Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering

1 code implementation NeurIPS 2020 Meng Liu, David F. Gleich

For this problem, we propose a novel generalization of random walk, diffusion, or smooth function methods in the literature to a convex p-norm cut function.

Community Detection Graph Clustering

Non-Local Graph Neural Networks

1 code implementation29 May 2020 Meng Liu, Zhengyang Wang, Shuiwang Ji

Modern graph neural networks (GNNs) learn node embeddings through multilayer local aggregation and achieve great success in applications on assortative graphs.

Node Classification on Non-Homophilic (Heterophilic) Graphs

KGAT: Knowledge Graph Attention Network for Recommendation

7 code implementations20 May 2019 Xiang Wang, Xiangnan He, Yixin Cao, Meng Liu, Tat-Seng Chua

To provide more accurate, diverse, and explainable recommendation, it is compulsory to go beyond modeling user-item interactions and take side information into account.

Explainable Recommendation Knowledge Graphs +1

Cost-Sensitive Feature Selection by Optimizing F-Measures

no code implementations4 Apr 2019 Meng Liu, Chang Xu, Yong Luo, Chao Xu, Yonggang Wen, DaCheng Tao

Feature selection is beneficial for improving the performance of general machine learning tasks by extracting an informative subset from the high-dimensional features.

Assessment of central serous chorioretinopathy (CSC) depicted on color fundus photographs using deep Learning

no code implementations14 Jan 2019 Yi Zhen, Hang Chen, Xu Zhang, Meng Liu, Xin Meng, Jian Zhang, Jiantao Pu

To investigate whether and to what extent central serous chorioretinopathy (CSC) depicted on color fundus photographs can be assessed using deep learning technology.

Sparsely Grouped Multi-task Generative Adversarial Networks for Facial Attribute Manipulation

2 code implementations19 May 2018 Jichao Zhang, Yezhi Shu, Songhua Xu, Gongze Cao, Fan Zhong, Meng Liu, Xueying Qin

To overcome such a key limitation, we propose Sparsely Grouped Generative Adversarial Networks (SG-GAN) as a novel approach that can translate images on sparsely grouped datasets where only a few samples for training are labelled.

Image-to-Image Translation Multi-Task Learning +2

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