Tsinghua University

∙ 北京 , China ∙ 0 followers

Tsinghua University is a major research university in Beijing, and a member of the elite C9 League of Chinese universities.

Stable Prediction with Model Misspecification and Agnostic Distribution Shift

For many machine learning algorithms, two main assumptions are required ...
01/31/2020 ∙ by Kun Kuang, et al. ∙ 95 ∙ share

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Graph Neural Networks: A Review of Methods and Applications

Lots of learning tasks require dealing with graph data which contains ri...
12/20/2018 ∙ by Jie Zhou, et al. ∙ 62 ∙ share

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Graph Random Neural Network

Graph neural networks (GNNs) have generalized deep learning methods into...
05/22/2020 ∙ by Wenzheng Feng, et al. ∙ 57 ∙ share

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Deep Learning on Graphs: A Survey

Deep learning has been shown successful in a number of domains, ranging ...
12/11/2018 ∙ by Ziwei Zhang, et al. ∙ 46 ∙ share

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Hierarchical Reinforcement Learning with Advantage-Based Auxiliary Rewards

Hierarchical Reinforcement Learning (HRL) is a promising approach to sol...
10/10/2019 ∙ by Siyuan Li, et al. ∙ 37 ∙ share

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6D Object Pose Regression via Supervised Learning on Point Clouds

This paper addresses the task of estimating the 6 degrees of freedom pos...
01/24/2020 ∙ by Ge Gao, et al. ∙ 37 ∙ share

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Functional Variational Bayesian Neural Networks

Variational Bayesian neural networks (BNNs) perform variational inferenc...
03/14/2019 ∙ by Shengyang Sun, et al. ∙ 34 ∙ share

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Quantum Adversarial Machine Learning

Adversarial machine learning is an emerging field that focuses on studyi...
12/31/2019 ∙ by Sirui Lu, et al. ∙ 34 ∙ share

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MQA: Answering the Question via Robotic Manipulation

In this paper,we propose a novel task of Manipulation Question Answering...
03/10/2020 ∙ by Yuhong Deng, et al. ∙ 34 ∙ share

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Roundtrip: A Deep Generative Neural Density Estimator

Density estimation is a fundamental problem in both statistics and machi...
04/20/2020 ∙ by Qiao Liu, et al. ∙ 32 ∙ share

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Exploring Frequency Domain Interpretation of Convolutional Neural Networks

Many existing interpretation methods of convolutional neural networks (C...
11/27/2019 ∙ by Zhongfan Jia, et al. ∙ 29 ∙ share

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SPI-Optimizer: an integral-Separated PI Controller for Stochastic Optimization

To overcome the oscillation problem in the classical momentum-based opti...
12/29/2018 ∙ by Dan Wang, et al. ∙ 28 ∙ share

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FaceShapeGene: A Disentangled Shape Representation for Flexible Face Image Editing

Existing methods for face image manipulation generally focus on editing ...
05/06/2019 ∙ by Sen-Zhe Xu, et al. ∙ 28 ∙ share

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Triple Generative Adversarial Networks

Generative adversarial networks (GANs) have shown promise in image gener...
12/20/2019 ∙ by Chongxuan Li, et al. ∙ 28 ∙ share

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SurfaceNet+: An End-to-end 3D Neural Network for Very Sparse Multi-view Stereopsis

Multi-view stereopsis (MVS) tries to recover the 3D model from 2D images...
05/26/2020 ∙ by Mengqi Ji, et al. ∙ 28 ∙ share

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Lossless Compression for 3DCNNs Based on Tensor Train Decomposition

Three dimensional convolutional neural networks (3DCNNs) have been appli...
12/08/2019 ∙ by Dingheng Wang, et al. ∙ 27 ∙ share

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Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets

We present a new loss function called Distribution-Balanced Loss for the...
07/19/2020 ∙ by Tong Wu, et al. ∙ 26 ∙ share

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DXSLAM: A Robust and Efficient Visual SLAM System with Deep Features

A robust and efficient Simultaneous Localization and Mapping (SLAM) syst...
08/12/2020 ∙ by Dongjiang Li, et al. ∙ 26 ∙ share

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Graph Policy Network for Transferable Active Learning on Graphs

Graph neural networks (GNNs) have been attracting increasing popularity ...
06/24/2020 ∙ by Shengding Hu, et al. ∙ 25 ∙ share

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Pruning from Scratch

Network pruning is an important research field aiming at reducing comput...
09/27/2019 ∙ by Yulong Wang, et al. ∙ 24 ∙ share

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Convolutional Networks with Dense Connectivity

Recent work has shown that convolutional networks can be substantially d...
01/08/2020 ∙ by Gao Huang, et al. ∙ 24 ∙ share

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Understanding Negative Sampling in Graph Representation Learning

Graph representation learning has been extensively studied in recent yea...
05/20/2020 ∙ by Zhen Yang, et al. ∙ 24 ∙ share

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Monocular Depth Prediction Through Continuous 3D Loss

This paper reports a new continuous 3D loss function for learning depth ...
03/21/2020 ∙ by Minghan Zhu, et al. ∙ 23 ∙ share

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DotFAN: A Domain-transferred Face Augmentation Network for Pose and Illumination Invariant Face Recognition

The performance of a convolutional neural network (CNN) based face recog...
02/23/2020 ∙ by Hao-Chiang Shao, et al. ∙ 22 ∙ share

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Eigen-GNN: A Graph Structure Preserving Plug-in for GNNs

Graph Neural Networks (GNNs) are emerging machine learning models on gra...
06/08/2020 ∙ by Ziwei Zhang, et al. ∙ 22 ∙ share

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DeepObfuscator: Adversarial Training Framework for Privacy-Preserving Image Classification

Deep learning has been widely utilized in many computer vision applicati...
09/09/2019 ∙ by Ang Li, et al. ∙ 21 ∙ share

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Transparent Classification with Multilayer Logical Perceptrons and Random Binarization

Models with transparent inner structure and high classification performa...
12/10/2019 ∙ by Zhuo Wang, et al. ∙ 21 ∙ share

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SeqXY2SeqZ: Structure Learning for 3D Shapes by Sequentially Predicting 1D Occupancy Segments From 2D Coordinates

Structure learning for 3D shapes is vital for 3D computer vision. State-...
03/12/2020 ∙ by Zhizhong Han, et al. ∙ 21 ∙ share

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KFNet: Learning Temporal Camera Relocalization using Kalman Filtering

Temporal camera relocalization estimates the pose with respect to each v...
03/24/2020 ∙ by Lei Zhou, et al. ∙ 21 ∙ share

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Deep Face Super-Resolution with Iterative Collaboration between Attentive Recovery and Landmark Estimation

Recent works based on deep learning and facial priors have succeeded in ...
03/29/2020 ∙ by Cheng Ma, et al. ∙ 21 ∙ share

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Theoretical Analysis of Auto Rate-Tuning by Batch Normalization

Batch Normalization (BN) has become a cornerstone of deep learning acros...
12/10/2018 ∙ by Sanjeev Arora, et al. ∙ 20 ∙ share

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Rule-Guided Compositional Representation Learning on Knowledge Graphs

Representation learning on a knowledge graph (KG) is to embed entities a...
11/20/2019 ∙ by Guanglin Niu, et al. ∙ 20 ∙ share

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Less Is Better: Unweighted Data Subsampling via Influence Function

In the time of Big Data, training complex models on large-scale data set...
12/03/2019 ∙ by Zifeng Wang, et al. ∙ 20 ∙ share

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TransMoMo: Invariance-Driven Unsupervised Video Motion Retargeting

We present a lightweight video motion retargeting approach TransMoMo tha...
03/31/2020 ∙ by Zhuoqian Yang, et al. ∙ 19 ∙ share

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LapEPI-Net: A Laplacian Pyramid EPI structure for Learning-based Dense Light Field Reconstruction

For dense sampled light field (LF) reconstruction problem, existing appr...
02/17/2019 ∙ by Gaochang Wu, et al. ∙ 18 ∙ share

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Unified Visual-Semantic Embeddings: Bridging Vision and Language with Structured Meaning Representations

We propose the Unified Visual-Semantic Embeddings (Unified VSE) for lear...
04/11/2019 ∙ by Hao Wu, et al. ∙ 18 ∙ share

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Deep Learning-Based Strategy for Macromolecules Classification with Imbalanced Data from Cellular Electron Cryotomography

Deep learning model trained by imbalanced data may not work satisfactori...
08/27/2019 ∙ by Ziqian Luo, et al. ∙ 18 ∙ share

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End-to-End Face Parsing via Interlinked Convolutional Neural Networks

Face parsing is an important computer vision task that requires accurate...
02/12/2020 ∙ by Zi Yin, et al. ∙ 18 ∙ share

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Hierarchical Feature Embedding for Attribute Recognition

Attribute recognition is a crucial but challenging task due to viewpoint...
05/23/2020 ∙ by Jie Yang, et al. ∙ 18 ∙ share

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Attention: to Better Stand on the Shoulders of Giants

Science of science (SciSci) is an emerging discipline wherein science is...
05/27/2020 ∙ by Sha Yuan, et al. ∙ 18 ∙ share

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Point2SpatialCapsule: Aggregating Features and Spatial Relationships of Local Regions on Point Clouds using Spatial-aware Capsules

Learning discriminative shape representation directly on point clouds is...
08/29/2019 ∙ by Xin Wen, et al. ∙ 17 ∙ share

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Temporal Interlacing Network

For a long time, the vision community tries to learn the spatio-temporal...
01/17/2020 ∙ by Hao Shao, et al. ∙ 17 ∙ share

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Attacking Optical Character Recognition (OCR) Systems with Adversarial Watermarks

Optical character recognition (OCR) is widely applied in real applicatio...
02/08/2020 ∙ by Lu Chen, et al. ∙ 17 ∙ share

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Bridging the Theoretical Bound and Deep Algorithms for Open Set Domain Adaptation

In the unsupervised open set domain adaptation (UOSDA), the target domai...
06/23/2020 ∙ by Li Zhong, et al. ∙ 17 ∙ share

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t-k-means: A k-means Variant with Robustness and Stability

Lloyd's k-means algorithm is one of the most classical clustering method...
07/17/2019 ∙ by Yang Zhang, et al. ∙ 16 ∙ share

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Implicit Semantic Data Augmentation for Deep Networks

In this paper, we propose a novel implicit semantic data augmentation (I...
09/26/2019 ∙ by Yulin Wang, et al. ∙ 16 ∙ share

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Morphing and Sampling Network for Dense Point Cloud Completion

3D point cloud completion, the task of inferring the complete geometric ...
11/30/2019 ∙ by Minghua Liu, et al. ∙ 16 ∙ share

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Scalable NAS with Factorizable Architectural Parameters

Neural architecture search (NAS) is an emerging topic in machine learnin...
12/31/2019 ∙ by Lanfei Wang, et al. ∙ 16 ∙ share

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Alchemy: A Quantum Chemistry Dataset for Benchmarking AI Models

We introduce a new molecular dataset, named Alchemy, for developing mach...
06/22/2019 ∙ by Guangyong Chen, et al. ∙ 15 ∙ share

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A Pre-training Based Personalized Dialogue Generation Model with Persona-sparse Data

Endowing dialogue systems with personas is essential to deliver more hum...
11/12/2019 ∙ by Yinhe Zheng, et al. ∙ 15 ∙ share

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