Tsinghua University

research

∙ 01/05/2022

Quantum Capsule Networks

Capsule networks, which incorporate the paradigms of connectionism and s...

Zidu Liu, et al. ∙

research

∙ 01/31/2020

Stable Prediction with Model Misspecification and Agnostic Distribution Shift

For many machine learning algorithms, two main assumptions are required ...

Kun Kuang, et al. ∙

research

∙ 03/17/2021

PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning

The predictive learning of spatiotemporal sequences aims to generate fut...

Yunbo Wang, et al. ∙

research

∙ 12/20/2018

Graph Neural Networks: A Review of Methods and Applications

Lots of learning tasks require dealing with graph data which contains ri...

Jie Zhou, et al. ∙

research

∙ 05/22/2020

Graph Random Neural Network

Graph neural networks (GNNs) have generalized deep learning methods into...

Wenzheng Feng, et al. ∙

research

∙ 03/15/2021

Learning Frequency-aware Dynamic Network for Efficient Super-Resolution

Deep learning based methods, especially convolutional neural networks (C...

Wenbin Xie, et al. ∙

research

∙ 12/11/2018

Deep Learning on Graphs: A Survey

Deep learning has been shown successful in a number of domains, ranging ...

Ziwei Zhang, et al. ∙

research

∙ 11/26/2021

Cyclic Graph Attentive Match Encoder (CGAME): A Novel Neural Network For OD Estimation

Origin-Destination Estimation plays an important role in traffic managem...

Guanzhou Li, et al. ∙

research

∙ 12/31/2021

Data-Free Knowledge Transfer: A Survey

In the last decade, many deep learning models have been well trained and...

Yuang Liu, et al. ∙

research

∙ 04/17/2021

RefineMask: Towards High-Quality Instance Segmentation with Fine-Grained Features

The two-stage methods for instance segmentation, e.g. Mask R-CNN, have a...

Gang Zhang, et al. ∙

research

∙ 11/07/2021

NLP From Scratch Without Large-Scale Pretraining: A Simple and Efficient Framework

Pretrained language models have become the standard approach for many NL...

Xingcheng Yao, et al. ∙

research

∙ 10/10/2019

Hierarchical Reinforcement Learning with Advantage-Based Auxiliary Rewards

Hierarchical Reinforcement Learning (HRL) is a promising approach to sol...

Siyuan Li, et al. ∙

research

∙ 01/24/2020

6D Object Pose Regression via Supervised Learning on Point Clouds

This paper addresses the task of estimating the 6 degrees of freedom pos...

Ge Gao, et al. ∙

research

∙ 11/15/2021

AI in Games: Techniques, Challenges and Opportunities

With breakthrough of AlphaGo, AI in human-computer game has become a ver...

Qiyue Yin, et al. ∙

research

∙ 03/14/2019

Functional Variational Bayesian Neural Networks

Variational Bayesian neural networks (BNNs) perform variational inferenc...

Shengyang Sun, et al. ∙

research

∙ 12/31/2019

Quantum Adversarial Machine Learning

Adversarial machine learning is an emerging field that focuses on studyi...

Sirui Lu, et al. ∙

research

∙ 03/10/2020

MQA: Answering the Question via Robotic Manipulation

In this paper,we propose a novel task of Manipulation Question Answering...

Yuhong Deng, et al. ∙

research

∙ 04/20/2020

Roundtrip: A Deep Generative Neural Density Estimator

Density estimation is a fundamental problem in both statistics and machi...

Qiao Liu, et al. ∙

research

∙ 11/27/2019

Exploring Frequency Domain Interpretation of Convolutional Neural Networks

Many existing interpretation methods of convolutional neural networks (C...

Zhongfan Jia, et al. ∙

research

∙ 01/21/2021

Monitoring nonstationary processes based on recursive cointegration analysis and elastic weight consolidation

This paper considers the problem of nonstationary process monitoring und...

Jingxin Zhang, et al. ∙

research

∙ 12/29/2018

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

To overcome the oscillation problem in the classical momentum-based opti...

Dan Wang, et al. ∙

research

∙ 05/06/2019

FaceShapeGene: A Disentangled Shape Representation for Flexible Face Image Editing

Existing methods for face image manipulation generally focus on editing ...

Sen-Zhe Xu, et al. ∙

research

∙ 12/20/2019

Triple Generative Adversarial Networks

Generative adversarial networks (GANs) have shown promise in image gener...

Chongxuan Li, et al. ∙

research

∙ 05/26/2020

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...

Mengqi Ji, et al. ∙

research

∙ 12/08/2019

Lossless Compression for 3DCNNs Based on Tensor Train Decomposition

Three dimensional convolutional neural networks (3DCNNs) have been appli...

Dingheng Wang, et al. ∙

research

∙ 07/19/2020

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

We present a new loss function called Distribution-Balanced Loss for the...

Tong Wu, et al. ∙

research

∙ 08/12/2020

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

A robust and efficient Simultaneous Localization and Mapping (SLAM) syst...

Dongjiang Li, et al. ∙

research

∙ 03/23/2022

Scale-Equivalent Distillation for Semi-Supervised Object Detection

Recent Semi-Supervised Object Detection (SS-OD) methods are mainly based...

Qiushan Guo, et al. ∙

research

∙ 06/24/2020

Graph Policy Network for Transferable Active Learning on Graphs

Graph neural networks (GNNs) have been attracting increasing popularity ...

Shengding Hu, et al. ∙

research

∙ 08/30/2021

Efficient Visual Recognition with Deep Neural Networks: A Survey on Recent Advances and New Directions

Visual recognition is currently one of the most important and active res...

Yang Wu, et al. ∙

research

∙ 09/26/2021

Entity Linking Meets Deep Learning: Techniques and Solutions

Entity linking (EL) is the process of linking entity mentions appearing ...

Wei Shen, et al. ∙

research

∙ 09/27/2019

Pruning from Scratch

Network pruning is an important research field aiming at reducing comput...

Yulong Wang, et al. ∙

research

∙ 01/08/2020

Convolutional Networks with Dense Connectivity

Recent work has shown that convolutional networks can be substantially d...

Gao Huang, et al. ∙

research

∙ 05/20/2020

Understanding Negative Sampling in Graph Representation Learning

Graph representation learning has been extensively studied in recent yea...

Zhen Yang, et al. ∙

research

∙ 03/15/2021

S-AT GCN: Spatial-Attention Graph Convolution Network based Feature Enhancement for 3D Object Detection

3D object detection plays a crucial role in environmental perception for...

Li Wang, et al. ∙

research

∙ 08/23/2021

Deep Relational Metric Learning

This paper presents a deep relational metric learning (DRML) framework f...

Wenzhao Zheng, et al. ∙

research

∙ 03/21/2020

Monocular Depth Prediction Through Continuous 3D Loss

This paper reports a new continuous 3D loss function for learning depth ...

Minghan Zhu, et al. ∙

research

∙ 03/17/2021

Implicit Normalizing Flows

Normalizing flows define a probability distribution by an explicit inver...

Cheng Lu, et al. ∙

research

∙ 07/29/2021

Tianshou: a Highly Modularized Deep Reinforcement Learning Library

We present Tianshou, a highly modularized python library for deep reinfo...

Jiayi Weng, et al. ∙

research

∙ 03/28/2022

LiDAR Distillation: Bridging the Beam-Induced Domain Gap for 3D Object Detection

In this paper, we propose the LiDAR Distillation to bridge the domain ga...

Yi Wei, et al. ∙

research

∙ 02/23/2020

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...

Hao-Chiang Shao, et al. ∙

research

∙ 06/08/2020

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

Graph Neural Networks (GNNs) are emerging machine learning models on gra...

Ziwei Zhang, et al. ∙

research

∙ 05/31/2022

Improved Vector Quantized Diffusion Models

Vector quantized diffusion (VQ-Diffusion) is a powerful generative model...

Zhicong Tang, et al. ∙

research

∙ 06/08/2022

Hub-Pathway: Transfer Learning from A Hub of Pre-trained Models

Transfer learning aims to leverage knowledge from pre-trained models to ...

Yang Shu, et al. ∙

research

∙ 09/09/2019

DeepObfuscator: Adversarial Training Framework for Privacy-Preserving Image Classification

Deep learning has been widely utilized in many computer vision applicati...

Ang Li, et al. ∙

research

∙ 12/10/2019

Transparent Classification with Multilayer Logical Perceptrons and Random Binarization

Models with transparent inner structure and high classification performa...

Zhuo Wang, et al. ∙

research

∙ 03/12/2020

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-...

Zhizhong Han, et al. ∙

research

∙ 03/24/2020

KFNet: Learning Temporal Camera Relocalization using Kalman Filtering

Temporal camera relocalization estimates the pose with respect to each v...

Lei Zhou, et al. ∙

research

∙ 03/29/2020

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 ...

Cheng Ma, et al. ∙

research

∙ 09/30/2021

Scalable Rule-Based Representation Learning for Interpretable Classification

Rule-based models, e.g., decision trees, are widely used in scenarios de...

Zhuo Wang, et al. ∙

Tsinghua University

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