Search Results for author: Yiwei Wang

Found 24 papers, 9 papers with code

Learning Progressive Joint Propagation for Human Motion Prediction

no code implementations ECCV 2020 Yujun Cai, Lin Huang, Yiwei Wang, Tat-Jen Cham, Jianfei Cai, Junsong Yuan, Jun Liu, Xu Yang, Yiheng Zhu, Xiaohui Shen, Ding Liu, Jing Liu, Nadia Magnenat Thalmann

Last, in order to incorporate a general motion space for high-quality prediction, we build a memory-based dictionary, which aims to preserve the global motion patterns in training data to guide the predictions.

Human motion prediction motion prediction

A Causal View of Entity Bias in (Large) Language Models

no code implementations24 May 2023 Fei Wang, Wenjie Mo, Yiwei Wang, Wenxuan Zhou, Muhao Chen

Meanwhile, our in-context intervention effectively reduces the knowledge conflicts between parametric knowledge and contextual knowledge in GPT-3. 5 and improves the F1 score by 9. 14 points on a challenging test set derived from Re-TACRED.

Relation Extraction

How Fragile is Relation Extraction under Entity Replacements?

1 code implementation22 May 2023 Yiwei Wang, Bryan Hooi, Fei Wang, Yujun Cai, Yuxuan Liang, Wenxuan Zhou, Jing Tang, Manjuan Duan, Muhao Chen

In principle, textual context determines the ground-truth relation and the RE models should be able to correctly identify the relations reflected by the textual context.

Benchmarking Causal Inference +1

AirFormer: Predicting Nationwide Air Quality in China with Transformers

1 code implementation29 Nov 2022 Yuxuan Liang, Yutong Xia, Songyu Ke, Yiwei Wang, Qingsong Wen, Junbo Zhang, Yu Zheng, Roger Zimmermann

Air pollution is a crucial issue affecting human health and livelihoods, as well as one of the barriers to economic and social growth.

Flashlight: Scalable Link Prediction with Effective Decoders

no code implementations17 Sep 2022 Yiwei Wang, Bryan Hooi, Yozen Liu, Tong Zhao, Zhichun Guo, Neil Shah

However, HadamardMLP lacks the scalability for retrieving top scoring neighbors on large graphs, since to the best of our knowledge, there does not exist an algorithm to retrieve the top scoring neighbors for HadamardMLP decoders in sublinear complexity.

Graph Learning Link Prediction

GRAPHCACHE: Message Passing as Caching for Sentence-Level Relation Extraction

no code implementations Findings (NAACL) 2022 Yiwei Wang, Muhao Chen, Wenxuan Zhou, Yujun Cai, Yuxuan Liang, Bryan Hooi

GRAPHCACHE aggregates the features from sentences in the whole dataset to learn global representations of properties, and use them to augment the local features within individual sentences.

Relation Extraction

Should We Rely on Entity Mentions for Relation Extraction? Debiasing Relation Extraction with Counterfactual Analysis

1 code implementation NAACL 2022 Yiwei Wang, Muhao Chen, Wenxuan Zhou, Yujun Cai, Yuxuan Liang, Dayiheng Liu, Baosong Yang, Juncheng Liu, Bryan Hooi

In this paper, we propose the CORE (Counterfactual Analysis based Relation Extraction) debiasing method that guides the RE models to focus on the main effects of textual context without losing the entity information.

Relation Extraction

Proximal Implicit ODE Solvers for Accelerating Learning Neural ODEs

no code implementations19 Apr 2022 Justin Baker, Hedi Xia, Yiwei Wang, Elena Cherkaev, Akil Narayan, Long Chen, Jack Xin, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang

Learning neural ODEs often requires solving very stiff ODE systems, primarily using explicit adaptive step size ODE solvers.

EIGNN: Efficient Infinite-Depth Graph Neural Networks

1 code implementation NeurIPS 2021 Juncheng Liu, Kenji Kawaguchi, Bryan Hooi, Yiwei Wang, Xiaokui Xiao

Motivated by this limitation, we propose a GNN model with infinite depth, which we call Efficient Infinite-Depth Graph Neural Networks (EIGNN), to efficiently capture very long-range dependencies.

Time-Aware Neighbor Sampling for Temporal Graph Networks

no code implementations18 Dec 2021 Yiwei Wang, Yujun Cai, Yuxuan Liang, Henghui Ding, Changhu Wang, Bryan Hooi

In this work, we propose the TNS (Time-aware Neighbor Sampling) method: TNS learns from temporal information to provide an adaptive receptive neighborhood for every node at any time.

Node Classification

Adaptive Data Augmentation on Temporal Graphs

no code implementations NeurIPS 2021 Yiwei Wang, Yujun Cai, Yuxuan Liang, Henghui Ding, Changhu Wang, Siddharth Bhatia, Bryan Hooi

To address this issue, our idea is to transform the temporal graphs using data augmentation (DA) with adaptive magnitudes, so as to effectively augment the input features and preserve the essential semantic information.

Data Augmentation Node Classification

Structure-Aware Label Smoothing for Graph Neural Networks

no code implementations1 Dec 2021 Yiwei Wang, Yujun Cai, Yuxuan Liang, Wei Wang, Henghui Ding, Muhao Chen, Jing Tang, Bryan Hooi

Representing a label distribution as a one-hot vector is a common practice in training node classification models.

Classification Node Classification

A Deterministic Sampling Method via Maximum Mean Discrepancy Flow with Adaptive Kernel

no code implementations21 Nov 2021 Yindong Chen, Yiwei Wang, Lulu Kang, Chun Liu

We propose a novel deterministic sampling method to approximate a target distribution $\rho^*$ by minimizing the kernel discrepancy, also known as the Maximum Mean Discrepancy (MMD).

Numerical Integration Variational Inference

GraphAnoGAN: Detecting Anomalous Snapshots from Attributed Graphs

1 code implementation29 Jun 2021 Siddharth Bhatia, Yiwei Wang, Bryan Hooi, Tanmoy Chakraborty

Specifically, the generative model learns to approximate the distribution of anomalous samples from the candidate set of graph snapshots, and the discriminative model detects whether the sampled snapshot is from the ground-truth or not.

Leveraging Large-Scale Weakly Labeled Data for Semi-Supervised Mass Detection in Mammograms

no code implementations CVPR 2021 Yuxing Tang, Zhenjie Cao, Yanbo Zhang, Zhicheng Yang, Zongcheng Ji, Yiwei Wang, Mei Han, Jie Ma, Jing Xiao, Peng Chang

Starting with a fully supervised model trained on the data with pixel-level masks, the proposed framework iteratively refines the model itself using the entire weakly labeled data (image-level soft label) in a self-training fashion.

Mixup for Node and Graph Classification

1 code implementation1 Jun 2021 Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Bryan Hooi

In this work, we propose the Mixup methods for two fundamental tasks in graph learning: node and graph classification.

Data Augmentation Graph Classification +2

Global Existence of Classical Solutions for a Reactive Polymeric Fluid near Equilibrium

no code implementations27 Jan 2021 Chun Liu, Yiwei Wang, Teng-Fei Zhang

In this paper, we study a new micro-macro model for a reactive polymeric fluid, which is derived recently in [Y. Wang, T.-F. Zhang, and C. Liu, \emph{J. Non-Newton.

Analysis of PDEs 35A01, 35A15, 76A10, 76M30, 82D60

A Unified 3D Human Motion Synthesis Model via Conditional Variational Auto-Encoder

no code implementations ICCV 2021 Yujun Cai, Yiwei Wang, Yiheng Zhu, Tat-Jen Cham, Jianfei Cai, Junsong Yuan, Jun Liu, Chuanxia Zheng, Sijie Yan, Henghui Ding, Xiaohui Shen, Ding Liu, Nadia Magnenat Thalmann

Notably, by considering this problem as a conditional generation process, we estimate a parametric distribution of the missing regions based on the input conditions, from which to sample and synthesize the full motion series.

motion prediction Motion Synthesis

LSCALE: Latent Space Clustering-Based Active Learning for Node Classification

1 code implementation13 Dec 2020 Juncheng Liu, Yiwei Wang, Bryan Hooi, Renchi Yang, Xiaokui Xiao

We argue that the representation power in unlabelled nodes can be useful for active learning and for further improving performance of active learning for node classification.

Active Learning General Classification +1

GraphCrop: Subgraph Cropping for Graph Classification

no code implementations22 Sep 2020 Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Bryan Hooi

We present a new method to regularize graph neural networks (GNNs) for better generalization in graph classification.

Data Augmentation General Classification +1

Particle-based Energetic Variational Inference

1 code implementation14 Apr 2020 Yiwei Wang, Jiuhai Chen, Chun Liu, Lulu Kang

Using the EVI framework, we can derive many existing Particle-based Variational Inference (ParVI) methods, including the popular Stein Variational Gradient Descent (SVGD) approach.

Variational Inference

Revisiting Convolutional Neural Networks for Citywide Crowd Flow Analytics

1 code implementation28 Feb 2020 Yuxuan Liang, Kun Ouyang, Yiwei Wang, Ye Liu, Junbo Zhang, Yu Zheng, David S. Rosenblum

This framework consists of three parts: 1) a local feature extraction module to learn representations for each region; 2) a global context module to extract global contextual priors and upsample them to generate the global features; and 3) a region-specific predictor based on tensor decomposition to provide customized predictions for each region, which is very parameter-efficient compared to previous methods.

Tensor Decomposition

How Shall I Drive? Interaction Modeling and Motion Planning towards Empathetic and Socially-Graceful Driving

no code implementations28 Jan 2019 Yi Ren, Steven Elliott, Yiwei Wang, Yezhou Yang, Wenlong Zhang

While intelligence of autonomous vehicles (AVs) has significantly advanced in recent years, accidents involving AVs suggest that these autonomous systems lack gracefulness in driving when interacting with human drivers.

Robotics Computer Science and Game Theory

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