Search Results for author: Yixin Chen

Found 82 papers, 40 papers with code

Highly Accurate Disease Diagnosis and Highly Reproducible Biomarker Identification with PathFormer

no code implementations11 Feb 2024 Zehao Dong, Qihang Zhao, Philip R. O. Payne, Michael A Province, Carlos Cruchaga, Muhan Zhang, Tianyu Zhao, Yixin Chen, Fuhai Li

However, we found two major limitations of existing GNNs in omics data analysis, i. e., limited-prediction (diagnosis) accuracy and limited-reproducible biomarker identification capacity across multiple datasets.

Large Language Model Meets Graph Neural Network in Knowledge Distillation

no code implementations8 Feb 2024 Shengxiang Hu, Guobing Zou, Song Yang, Yanglan Gan, Bofeng Zhang, Yixin Chen

Despite recent community revelations about the advancements and potential applications of Large Language Models (LLMs) in understanding Text-Attributed Graph (TAG), the deployment of LLMs for production is hindered by its high computational and storage requirements, as well as long latencies during model inference.

Contrastive Learning Knowledge Distillation +4

DoseGNN: Improving the Performance of Deep Learning Models in Adaptive Dose-Volume Histogram Prediction through Graph Neural Networks

no code implementations2 Feb 2024 Zehao Dong, Yixin Chen, Tianyu Zhao

Dose-Volume Histogram (DVH) prediction is fundamental in radiation therapy that facilitate treatment planning, dose evaluation, plan comparison and etc.

TFDMNet: A Novel Network Structure Combines the Time Domain and Frequency Domain Features

1 code implementation29 Jan 2024 Hengyue Pan, Yixin Chen, Zhiliang Tian, Peng Qiao, Linbo Qiao, Dongsheng Li

To get the balance between the computation complexity and memory usage, we propose a new network structure, namely Time-Frequency Domain Mixture Network (TFDMNet), which combines the advantages of both convolution layers and EMLs.

A Systematic Literature Review on Explainability for Machine/Deep Learning-based Software Engineering Research

no code implementations26 Jan 2024 Sicong Cao, Xiaobing Sun, Ratnadira Widyasari, David Lo, Xiaoxue Wu, Lili Bo, Jiale Zhang, Bin Li, Wei Liu, Di wu, Yixin Chen

The remarkable achievements of Artificial Intelligence (AI) algorithms, particularly in Machine Learning (ML) and Deep Learning (DL), have fueled their extensive deployment across multiple sectors, including Software Engineering (SE).

Decision Making Vulnerability Detection

Topology-aware Embedding Memory for Continual Learning on Expanding Networks

no code implementations24 Jan 2024 Xikun Zhang, Dongjin Song, Yixin Chen, DaCheng Tao

Memory replay based techniques have shown great success for continual learning with incrementally accumulated Euclidean data.

Continual Learning

Toward Robust Multimodal Learning using Multimodal Foundational Models

no code implementations20 Jan 2024 Xianbing Zhao, Soujanya Poria, Xuejiao Li, Yixin Chen, Buzhou Tang

Recently, CLIP-based multimodal foundational models have demonstrated impressive performance on numerous multimodal tasks by learning the aligned cross-modal semantics of image and text pairs, but the multimodal foundational models are also unable to directly address scenarios involving modality absence.

Multimodal Sentiment Analysis

Should ChatGPT Write Your Breakup Text? Exploring the Role of AI in Relationship Dissolution

no code implementations18 Jan 2024 Yue Fu, Yixin Chen, Zelia Gomes Da Costa Lai, Alexis Hiniker

We aim to understand: 1) the current role of technology in the breakup process, 2) the needs and support individuals have during the process, and 3) how AI might address these needs.

Blocking

SceneVerse: Scaling 3D Vision-Language Learning for Grounded Scene Understanding

no code implementations17 Jan 2024 Baoxiong Jia, Yixin Chen, Huangyue Yu, Yan Wang, Xuesong Niu, Tengyu Liu, Qing Li, Siyuan Huang

In comparison to recent advancements in the 2D domain, grounding language in 3D scenes faces several significant challenges: (i) the inherent complexity of 3D scenes due to the diverse object configurations, their rich attributes, and intricate relationships; (ii) the scarcity of paired 3D vision-language data to support grounded learning; and (iii) the absence of a unified learning framework to distill knowledge from grounded 3D data.

Scene Understanding Visual Grounding

CaMML: Context-Aware Multimodal Learner for Large Models

no code implementations6 Jan 2024 Yixin Chen, Shuai Zhang, Boran Han, Tong He, Bo Li

In this work, we introduce Context-Aware MultiModal Learner (CaMML), for tuning large multimodal models (LMMs).

Visual Question Answering

Single-view 3D Scene Reconstruction with High-fidelity Shape and Texture

no code implementations1 Nov 2023 Yixin Chen, Junfeng Ni, Nan Jiang, Yaowei Zhang, Yixin Zhu, Siyuan Huang

Reconstructing detailed 3D scenes from single-view images remains a challenging task due to limitations in existing approaches, which primarily focus on geometric shape recovery, overlooking object appearances and fine shape details.

3D Object Reconstruction 3D Reconstruction +5

PointHR: Exploring High-Resolution Architectures for 3D Point Cloud Segmentation

1 code implementation11 Oct 2023 Haibo Qiu, Baosheng Yu, Yixin Chen, DaCheng Tao

Significant progress has been made recently in point cloud segmentation utilizing an encoder-decoder framework, which initially encodes point clouds into low-resolution representations and subsequently decodes high-resolution predictions.

Point Cloud Segmentation Semantic Segmentation

Revisiting Plasticity in Visual Reinforcement Learning: Data, Modules and Training Stages

1 code implementation11 Oct 2023 Guozheng Ma, Lu Li, Sen Zhang, Zixuan Liu, Zhen Wang, Yixin Chen, Li Shen, Xueqian Wang, DaCheng Tao

Plasticity, the ability of a neural network to evolve with new data, is crucial for high-performance and sample-efficient visual reinforcement learning (VRL).

Data Augmentation reinforcement-learning

Parameter Efficient Multi-task Model Fusion with Partial Linearization

no code implementations7 Oct 2023 Anke Tang, Li Shen, Yong Luo, Yibing Zhan, Han Hu, Bo Du, Yixin Chen, DaCheng Tao

We demonstrate that our partial linearization technique enables a more effective fusion of multiple tasks into a single model, outperforming standard adapter tuning and task arithmetic alone.

One for All: Towards Training One Graph Model for All Classification Tasks

1 code implementation29 Sep 2023 Hao liu, Jiarui Feng, Lecheng Kong, Ningyue Liang, DaCheng Tao, Yixin Chen, Muhan Zhang

For in-context learning on graphs, OFA introduces a novel graph prompting paradigm that appends prompting substructures to the input graph, which enables it to address varied tasks without fine-tuning.

Graph Classification Graph Learning +3

GNNHLS: Evaluating Graph Neural Network Inference via High-Level Synthesis

1 code implementation27 Sep 2023 Chenfeng Zhao, Zehao Dong, Yixin Chen, Xuan Zhang, Roger D. Chamberlain

In this paper, we propose GNNHLS, an open-source framework to comprehensively evaluate GNN inference acceleration on FPGAs via HLS, containing a software stack for data generation and baseline deployment, and FPGA implementations of 6 well-tuned GNN HLS kernels.

FP-PET: Large Model, Multiple Loss And Focused Practice

no code implementations22 Sep 2023 Yixin Chen, Ourui Fu, Wenrui Shao, Zhaoheng Xie

This study presents FP-PET, a comprehensive approach to medical image segmentation with a focus on CT and PET images.

Image Segmentation Medical Image Segmentation +2

Graph Contrastive Learning Meets Graph Meta Learning: A Unified Method for Few-shot Node Tasks

1 code implementation19 Sep 2023 Hao liu, Jiarui Feng, Lecheng Kong, DaCheng Tao, Yixin Chen, Muhan Zhang

In our study, we first identify two crucial advantages of contrastive learning compared to meta learning, including (1) the comprehensive utilization of graph nodes and (2) the power of graph augmentations.

CoLA Contrastive Learning +3

CktGNN: Circuit Graph Neural Network for Electronic Design Automation

1 code implementation31 Aug 2023 Zehao Dong, Weidong Cao, Muhan Zhang, DaCheng Tao, Yixin Chen, Xuan Zhang

The electronic design automation of analog circuits has been a longstanding challenge in the integrated circuit field due to the huge design space and complex design trade-offs among circuit specifications.

Bayesian Optimization Graph Learning

3D-VisTA: Pre-trained Transformer for 3D Vision and Text Alignment

1 code implementation ICCV 2023 Ziyu Zhu, Xiaojian Ma, Yixin Chen, Zhidong Deng, Siyuan Huang, Qing Li

3D vision-language grounding (3D-VL) is an emerging field that aims to connect the 3D physical world with natural language, which is crucial for achieving embodied intelligence.

Dense Captioning Question Answering +3

PNT-Edge: Towards Robust Edge Detection with Noisy Labels by Learning Pixel-level Noise Transitions

1 code implementation26 Jul 2023 Wenjie Xuan, Shanshan Zhao, Yu Yao, Juhua Liu, Tongliang Liu, Yixin Chen, Bo Du, DaCheng Tao

Exploiting the estimated noise transitions, our model, named PNT-Edge, is able to fit the prediction to clean labels.

Edge Detection

Extending the Design Space of Graph Neural Networks by Rethinking Folklore Weisfeiler-Lehman

1 code implementation NeurIPS 2023 Jiarui Feng, Lecheng Kong, Hao liu, DaCheng Tao, Fuhai Li, Muhan Zhang, Yixin Chen

We theoretically prove that even if we fix the space complexity to $O(n^k)$ (for any $k\geq 2$) in $(k, t)$-FWL, we can construct an expressiveness hierarchy up to solving the graph isomorphism problem.

Graph Regression

Improving Heterogeneous Model Reuse by Density Estimation

1 code implementation23 May 2023 Anke Tang, Yong Luo, Han Hu, Fengxiang He, Kehua Su, Bo Du, Yixin Chen, DaCheng Tao

This paper studies multiparty learning, aiming to learn a model using the private data of different participants.

Density Estimation Selection bias

FVP: Fourier Visual Prompting for Source-Free Unsupervised Domain Adaptation of Medical Image Segmentation

no code implementations26 Apr 2023 Yan Wang, Jian Cheng, Yixin Chen, Shuai Shao, Lanyun Zhu, Zhenzhou Wu, Tao Liu, Haogang Zhu

In FVP, the visual prompt is parameterized using only a small amount of low-frequency learnable parameters in the input frequency space, and is learned by minimizing the segmentation loss between the predicted segmentation of the prompted target image and reliable pseudo segmentation label of the target image under the frozen model.

Image Segmentation Medical Image Segmentation +4

Recurrent Transformer for Dynamic Graph Representation Learning with Edge Temporal States

no code implementations20 Apr 2023 Shengxiang Hu, Guobing Zou, Shiyi Lin, Liangrui Wu, Chenyang Zhou, Bofeng Zhang, Yixin Chen

Dynamic graph representation learning is growing as a trending yet challenging research task owing to the widespread demand for graph data analysis in real world applications.

Dynamic Link Prediction Graph Representation Learning

Learning Context-aware Classifier for Semantic Segmentation

2 code implementations21 Mar 2023 Zhuotao Tian, Jiequan Cui, Li Jiang, Xiaojuan Qi, Xin Lai, Yixin Chen, Shu Liu, Jiaya Jia

Semantic segmentation is still a challenging task for parsing diverse contexts in different scenes, thus the fixed classifier might not be able to well address varying feature distributions during testing.

Segmentation Semantic Segmentation

Detecting Human-Object Contact in Images

1 code implementation CVPR 2023 Yixin Chen, Sai Kumar Dwivedi, Michael J. Black, Dimitrios Tzionas

To build HOT, we use two data sources: (1) We use the PROX dataset of 3D human meshes moving in 3D scenes, and automatically annotate 2D image areas for contact via 3D mesh proximity and projection.

Object

A Multi-View Joint Learning Framework for Embedding Clinical Codes and Text Using Graph Neural Networks

no code implementations27 Jan 2023 Lecheng Kong, Christopher King, Bradley Fritz, Yixin Chen

Learning to represent free text is a core task in many clinical machine learning (ML) applications, as clinical text contains observations and plans not otherwise available for inference.

MULTI-VIEW LEARNING

On Transforming Reinforcement Learning by Transformer: The Development Trajectory

no code implementations29 Dec 2022 Shengchao Hu, Li Shen, Ya zhang, Yixin Chen, DaCheng Tao

Transformer, originally devised for natural language processing, has also attested significant success in computer vision.

Autonomous Driving reinforcement-learning +2

Full-Body Articulated Human-Object Interaction

1 code implementation ICCV 2023 Nan Jiang, Tengyu Liu, Zhexuan Cao, Jieming Cui, Zhiyuan Zhang, Yixin Chen, He Wang, Yixin Zhu, Siyuan Huang

By learning the geometrical relationships in HOI, we devise the very first model that leverage human pose estimation to tackle the estimation of articulated object poses and shapes during whole-body interactions.

Action Recognition Human-Object Interaction Detection +3

Algorithmic Bias in Machine Learning Based Delirium Prediction

no code implementations8 Nov 2022 Sandhya Tripathi, Bradley A Fritz, Michael S Avidan, Yixin Chen, Christopher R King

Although prediction models for delirium, a commonly occurring condition during general hospitalization or post-surgery, have not gained huge popularity, their algorithmic bias evaluation is crucial due to the existing association between social determinants of health and delirium risk.

HUMANISE: Language-conditioned Human Motion Generation in 3D Scenes

no code implementations18 Oct 2022 Zan Wang, Yixin Chen, Tengyu Liu, Yixin Zhu, Wei Liang, Siyuan Huang

Learning to generate diverse scene-aware and goal-oriented human motions in 3D scenes remains challenging due to the mediocre characteristics of the existing datasets on Human-Scene Interaction (HSI); they only have limited scale/quality and lack semantics.

Scalable Distributed Algorithms for Size-Constrained Submodular Maximization in the MapReduce and Adaptive Complexity Models

no code implementations20 Jun 2022 Tonmoy Dey, Yixin Chen, Alan Kuhnle

Distributed maximization of a submodular function in the MapReduce model has received much attention, culminating in two frameworks that allow a centralized algorithm to be run in the MR setting without loss of approximation, as long as the centralized algorithm satisfies a certain consistency property - which had only been shown to be satisfied by the standard greedy and continous greedy algorithms.

How Powerful are K-hop Message Passing Graph Neural Networks

1 code implementation26 May 2022 Jiarui Feng, Yixin Chen, Fuhai Li, Anindya Sarkar, Muhan Zhang

Recently, researchers extended 1-hop message passing to K-hop message passing by aggregating information from K-hop neighbors of nodes simultaneously.

One-Class Model for Fabric Defect Detection

1 code implementation20 Apr 2022 Hao Zhou, Yixin Chen, David Troendle, Byunghyun Jang

Our model takes advantage of a well-designed Gabor filter bank to analyze fabric texture.

Defect Detection

Learning Convolutional Neural Networks in the Frequency Domain

2 code implementations14 Apr 2022 Hengyue Pan, Yixin Chen, Xin Niu, Wenbo Zhou, Dongsheng Li

The most important motivation of this research is that we can use the straightforward element-wise multiplication operation to replace the image convolution in the frequency domain based on the Cross-Correlation Theorem, which obviously reduces the computation complexity.

PACE: A Parallelizable Computation Encoder for Directed Acyclic Graphs

1 code implementation19 Mar 2022 Zehao Dong, Muhan Zhang, Fuhai Li, Yixin Chen

In this work, we propose a Parallelizable Attention-based Computation structure Encoder (PACE) that processes nodes simultaneously and encodes DAGs in parallel.

Neural Architecture Search

SEA: Bridging the Gap Between One- and Two-stage Detector Distillation via SEmantic-aware Alignment

no code implementations2 Mar 2022 Yixin Chen, Zhuotao Tian, Pengguang Chen, Shu Liu, Jiaya Jia

We revisit the one- and two-stage detector distillation tasks and present a simple and efficient semantic-aware framework to fill the gap between them.

Instance Segmentation object-detection +2

PartAfford: Part-level Affordance Discovery from 3D Objects

no code implementations28 Feb 2022 Chao Xu, Yixin Chen, He Wang, Song-Chun Zhu, Yixin Zhu, Siyuan Huang

We propose a novel learning framework for PartAfford, which discovers part-level representations by leveraging only the affordance set supervision and geometric primitive regularization, without dense supervision.

Object

Best of Both Worlds: Practical and Theoretically Optimal Submodular Maximization in Parallel

1 code implementation NeurIPS 2021 Yixin Chen, Tonmoy Dey, Alan Kuhnle

For the problem of maximizing a monotone, submodular function with respect to a cardinality constraint $k$ on a ground set of size $n$, we provide an algorithm that achieves the state-of-the-art in both its empirical performance and its theoretical properties, in terms of adaptive complexity, query complexity, and approximation ratio; that is, it obtains, with high probability, query complexity of $O(n)$ in expectation, adaptivity of $O(\log(n))$, and approximation ratio of nearly $1-1/e$.

Training Neural Networks for Solving 1-D Optimal Piecewise Linear Approximation

no code implementations14 Oct 2021 Hangcheng Dong, Jingxiao Liao, Yan Wang, Yixin Chen, Bingguo Liu, Dong Ye, Guodong Liu

Our main contributions are that we propose the theorems to characterize the optimal solution of the PWLA problem and present the LNN method for solving it.

Deep Structured Instance Graph for Distilling Object Detectors

1 code implementation ICCV 2021 Yixin Chen, Pengguang Chen, Shu Liu, LiWei Wang, Jiaya Jia

Effectively structuring deep knowledge plays a pivotal role in transfer from teacher to student, especially in semantic vision tasks.

Instance Segmentation Knowledge Distillation +5

YouRefIt: Embodied Reference Understanding with Language and Gesture

no code implementations ICCV 2021 Yixin Chen, Qing Li, Deqian Kong, Yik Lun Kei, Song-Chun Zhu, Tao Gao, Yixin Zhu, Siyuan Huang

To the best of our knowledge, this is the first embodied reference dataset that allows us to study referring expressions in daily physical scenes to understand referential behavior, human communication, and human-robot interaction.

CIM: Class-Irrelevant Mapping for Few-Shot Classification

no code implementations7 Sep 2021 Shuai Shao, Lei Xing, Yixin Chen, Yan-Jiang Wang, Bao-Di Liu, Yicong Zhou

(2) Use the FEM to extract the features of novel data (with few labeled samples and totally different categories from base data), then classify them with the to-be-designed classifier.

Classification Dictionary Learning +1

Exploring and Improving Mobile Level Vision Transformers

no code implementations30 Aug 2021 Pengguang Chen, Yixin Chen, Shu Liu, MingChang Yang, Jiaya Jia

We analyze the reason behind this phenomenon, and propose a novel irregular patch embedding module and adaptive patch fusion module to improve the performance.

A Modulation Layer to Increase Neural Network Robustness Against Data Quality Issues

1 code implementation19 Jul 2021 Mohamed Abdelhack, Jiaming Zhang, Sandhya Tripathi, Bradley A Fritz, Daniel Felsky, Michael S Avidan, Yixin Chen, Christopher R King

Data missingness and quality are common problems in machine learning, especially for high-stakes applications such as healthcare.

Imputation

Interpretable Drug Synergy Prediction with Graph Neural Networks for Human-AI Collaboration in Healthcare

no code implementations14 May 2021 Zehao Dong, Heming Zhang, Yixin Chen, Fuhai Li

Though deep learning algorithms are widely used in the drug synergy prediction problem, it is still an open problem to formulate the prediction model with biological meaning to investigate the mysterious mechanisms of synergy (MoS) for the human-AI collaboration in healthcare systems.

(Un)fairness in Post-operative Complication Prediction Models

no code implementations3 Nov 2020 Sandhya Tripathi, Bradley A. Fritz, Mohamed Abdelhack, Michael S. Avidan, Yixin Chen, Christopher R. King

With the current ongoing debate about fairness, explainability and transparency of machine learning models, their application in high-impact clinical decision-making systems must be scrutinized.

Decision Making Fairness

Practical and Parallelizable Algorithms for Non-Monotone Submodular Maximization with Size Constraint

1 code implementation3 Sep 2020 Yixin Chen, Alan Kuhnle

In this version, we propose a fixed and improved subroutine to add a set with high average marginal gain, ThreshSeq, which returns a solution in $O( \log(n) )$ adaptive rounds with high probability.

LEMMA: A Multi-view Dataset for Learning Multi-agent Multi-task Activities

1 code implementation ECCV 2020 Baoxiong Jia, Yixin Chen, Siyuan Huang, Yixin Zhu, Song-Chun Zhu

Understanding and interpreting human actions is a long-standing challenge and a critical indicator of perception in artificial intelligence.

Action Recognition Action Understanding +3

Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic Reasoning

1 code implementation ICML 2020 Qing Li, Siyuan Huang, Yining Hong, Yixin Chen, Ying Nian Wu, Song-Chun Zhu

In this paper, we address these issues and close the loop of neural-symbolic learning by (1) introducing the \textbf{grammar} model as a \textit{symbolic prior} to bridge neural perception and symbolic reasoning, and (2) proposing a novel \textbf{back-search} algorithm which mimics the top-down human-like learning procedure to propagate the error through the symbolic reasoning module efficiently.

Question Answering Reinforcement Learning (RL) +1

DEPARA: Deep Attribution Graph for Deep Knowledge Transferability

1 code implementation CVPR 2020 Jie Song, Yixin Chen, Jingwen Ye, Xinchao Wang, Chengchao Shen, Feng Mao, Mingli Song

In this paper, we propose the DEeP Attribution gRAph (DEPARA) to investigate the transferability of knowledge learned from PR-DNNs.

Model Selection Transfer Learning

PerspectiveNet: 3D Object Detection from a Single RGB Image via Perspective Points

no code implementations NeurIPS 2019 Siyuan Huang, Yixin Chen, Tao Yuan, Siyuan Qi, Yixin Zhu, Song-Chun Zhu

Detecting 3D objects from a single RGB image is intrinsically ambiguous, thus requiring appropriate prior knowledge and intermediate representations as constraints to reduce the uncertainties and improve the consistencies between the 2D image plane and the 3D world coordinate.

Ranked #2 on Monocular 3D Object Detection on SUN RGB-D (AP@0.15 (10 / PNet-30) metric)

Monocular 3D Object Detection Object +1

Deep Model Transferability from Attribution Maps

2 code implementations NeurIPS 2019 Jie Song, Yixin Chen, Xinchao Wang, Chengchao Shen, Mingli Song

Exploring the transferability between heterogeneous tasks sheds light on their intrinsic interconnections, and consequently enables knowledge transfer from one task to another so as to reduce the training effort of the latter.

Transfer Learning

Holistic++ Scene Understanding: Single-view 3D Holistic Scene Parsing and Human Pose Estimation with Human-Object Interaction and Physical Commonsense

no code implementations ICCV 2019 Yixin Chen, Siyuan Huang, Tao Yuan, Siyuan Qi, Yixin Zhu, Song-Chun Zhu

We propose a new 3D holistic++ scene understanding problem, which jointly tackles two tasks from a single-view image: (i) holistic scene parsing and reconstruction---3D estimations of object bounding boxes, camera pose, and room layout, and (ii) 3D human pose estimation.

3D Human Pose Estimation Human-Object Interaction Detection +1

A Factored Generalized Additive Model for Clinical Decision Support in the Operating Room

1 code implementation29 Jul 2019 Zhicheng Cui, Bradley A Fritz, Christopher R King, Michael S Avidan, Yixin Chen

In this paper, we propose a factored generalized additive model (F-GAM) to preserve the model interpretability for targeted features while allowing a rich model for interaction with features fixed within the individual.

Additive models Respiratory Failure

Graph Neural Lasso for Dynamic Network Regression

1 code implementation25 Jul 2019 Yixin Chen, Lin Meng, Jiawei Zhang

Experimental results provided on two networked sequence datasets, i. e., Nasdaq-100 and METR-LA, show that GNL can address the network regression problem very well and is also very competitive among the existing approaches.

regression

Inductive Matrix Completion Based on Graph Neural Networks

3 code implementations ICLR 2020 Muhan Zhang, Yixin Chen

Under the extreme setting where not any side information is available other than the matrix to complete, can we still learn an inductive matrix completion model?

Matrix Completion Recommendation Systems +1

Inferring Shared Attention in Social Scene Videos

no code implementations CVPR 2018 Lifeng Fan, Yixin Chen, Ping Wei, Wenguan Wang, Song-Chun Zhu

We collect a new dataset VideoCoAtt from public TV show videos, containing 380 complex video sequences with more than 492, 000 frames that include diverse social scenes for shared attention study.

Scene Understanding

Link Prediction Based on Graph Neural Networks

9 code implementations NeurIPS 2018 Muhan Zhang, Yixin Chen

The theory unifies a wide range of heuristics in a single framework, and proves that all these heuristics can be well approximated from local subgraphs.

Link Prediction

Weisfeiler-lehman neural machine for link prediction

1 code implementation KDD 2017 Muhan Zhang, Yixin Chen

Compared with traditional link prediction methods, Wlnm does not assume a particular link formation mechanism (such as common neighbors), but learns this mechanism from the graph itself.

Link Prediction

Multi-Scale Convolutional Neural Networks for Time Series Classification

2 code implementations22 Mar 2016 Zhicheng Cui, Wenlin Chen, Yixin Chen

These methods are ad-hoc and separate the feature extraction part with the classification part, which limits their accuracy performance.

Classification Dynamic Time Warping +4

Optimal Action Extraction for Random Forests and Boosted Trees

1 code implementation13 Aug 2015 Zhicheng Cui, Wenlin Chen, Yujie He, Yixin Chen

To address this problem, we present a novel framework to post-process any ATM classifier to extract an optimal actionable plan that can change a given input to a desired class with a minimum cost.

Compressing Convolutional Neural Networks

no code implementations14 Jun 2015 Wenlin Chen, James T. Wilson, Stephen Tyree, Kilian Q. Weinberger, Yixin Chen

Convolutional neural networks (CNN) are increasingly used in many areas of computer vision.

Compressing Neural Networks with the Hashing Trick

1 code implementation19 Apr 2015 Wenlin Chen, James T. Wilson, Stephen Tyree, Kilian Q. Weinberger, Yixin Chen

As deep nets are increasingly used in applications suited for mobile devices, a fundamental dilemma becomes apparent: the trend in deep learning is to grow models to absorb ever-increasing data set sizes; however mobile devices are designed with very little memory and cannot store such large models.

SAS+ Planning as Satisfiability

no code implementations18 Jan 2014 Ruoyun Huang, Yixin Chen, Weixiong Zhang

We prove the correctness of the new encoding by establishing an isomorphism between the solution plans of SASE and that of STRIPS based encodings.

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