
Deep Sketchguided Cartoon Video Synthesis
We propose a novel framework to produce cartoon videos by fetching the c...
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Training Interpretable Convolutional Neural Networks by Differentiating Classspecific Filters
Convolutional neural networks (CNNs) have been successfully used in a ra...
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Bridging preferencebased instrumental variable studies and clusterrandomized encouragement experiments: study design, noncompliance, and average cluster effect ratio
Instrumental variable methods are widely used in medical and social scie...
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Noisy Differentiable Architecture Search
Simplicity is the ultimate sophistication. Differentiable Architecture S...
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Bringing Old Photos Back to Life
We propose to restore old photos that suffer from severe degradation thr...
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Crossdomain Correspondence Learning for Exemplarbased Image Translation
We present a general framework for exemplarbased image translation, whi...
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Automatic, Dynamic, and Nearly Optimal Learning Rate Specification by Local Quadratic Approximation
In deep learning tasks, the learning rate determines the update step siz...
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Perceptual Image SuperResolution with Progressive Adversarial Network
Single Image SuperResolution (SISR) aims to improve resolution of small...
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Performance Analysis and Optimization in PrivacyPreserving Federated Learning
As a means of decentralized machine learning, federated learning (FL) ha...
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Selecting and ranking individualized treatment rules with unmeasured confounding
It is common to compare individualized treatment rules based on the valu...
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Beyond Clicks: Modeling MultiRelational Item Graph for SessionBased Target Behavior Prediction
Sessionbased target behavior prediction aims to predict the next item t...
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A Wasserstein Minimum Velocity Approach to Learning Unnormalized Models
Score matching provides an effective approach to learning flexible unnor...
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Estimating Optimal Treatment Rules with an Instrumental Variable: A Partial Identification Learning Approach
Individualized treatment rules (ITRs) are considered a promising recipe ...
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Estimating Optimal Treatment Rules with an Instrumental Variable: A SemiSupervised Learning Approach
Individualized treatment rules (ITRs) are regarded as a promising recipe...
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Imaging of buried obstacles in a twolayered medium with phaseless farfield data
The inverse problem we consider is to reconstruct the location and shape...
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Privacy for All: Demystify Vulnerability Disparity of Differential Privacy against Membership Inference Attack
Machine learning algorithms, when applied to sensitive data, pose a pote...
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MixPath: A Unified Approach for Oneshot Neural Architecture Search
The expressiveness of search space is a key concern in neural architectu...
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Neural Architecture Search on Acoustic Scene Classification
Convolutional neural networks are widely adopted in Acoustic Scene Class...
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Latent Variables on Spheres for Sampling and Spherical Inference
Variational inference is a fundamental problem in Variational AutoEncod...
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Triple Generative Adversarial Networks
Generative adversarial networks (GANs) have shown promise in image gener...
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Realization of spatial sparseness by deep ReLU nets with massive data
The great success of deep learning poses urgent challenges for understan...
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Automatic quality assessment for 2D fetal sonographic standard plane based on multitask learning
The quality control of fetal sonographic (FS) images is essential for th...
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Fair DARTS: Eliminating Unfair Advantages in Differentiable Architecture Search
Differential Architecture Search (DARTS) is now a widely disseminated we...
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DBSN: Measuring Uncertainty through Bayesian Learning of Deep Neural Network Structures
Bayesian neural networks (BNNs) introduce uncertainty estimation to deep...
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Instrumental Variables: to Strengthen or not to Strengthen?
Instrumental variables (IV) are extensively used to estimate treatment e...
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In Vitro Fertilization (IVF) Cumulative Pregnancy Rate Prediction from Basic Patient Characteristics
Tens of millions of women suffer from infertility worldwide each year. I...
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Regularized Adversarial Sampling and Deep Timeaware Attention for ClickThrough Rate Prediction
Improving the performance of clickthrough rate (CTR) prediction remains...
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A Semiparametric Approach to Modelbased Sensitivity Analysis in Observational Studies
When drawing causal inference from observational data, there is always c...
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Understanding and Stabilizing GANs' Training Dynamics with Control Theory
Generative adversarial networks (GANs) have made significant progress on...
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Pruning from Scratch
Network pruning is an important research field aiming at reducing comput...
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Document Rectification and Illumination Correction using a Patchbased CNN
We propose a novel learning method to rectify document images with vario...
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A DataCenter FPGA Acceleration Platform for Convolutional Neural Networks
Intensive computation is entering data centers with multiple workloads o...
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Blind Geometric Distortion Correction on Images Through Deep Learning
We propose the first general framework to automatically correct differen...
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MultiTask Deep Learning with Dynamic Programming for Embryo Early Development Stage Classification from TimeLapse Videos
Timelapse is a technology used to record the development of embryos dur...
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ScarletNAS: Bridging the Gap Between Scalability and Fairness in Neural Architecture Search
Oneshot neural architecture search features fast training of a supernet...
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An approximate factorization method for inverse acoustic scattering with phaseless nearfield data
This paper is concerned with the inverse acoustic scattering problem wit...
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MoGA: Searching Beyond MobileNetV3
The evolution of MobileNets has laid a solid foundation for neural netwo...
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Convergence of the perfectly matched layer method for transient acousticelastic interaction above an unbounded rough surface
This paper is concerned with the timedependent acousticelastic interac...
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Convergence analysis of the PML method for timedomain electromagnetic scattering problems
In this paper, a perfectly matched layer (PML) method is proposed to sol...
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FairNAS: Rethinking Evaluation Fairness of Weight Sharing Neural Architecture Search
The ability to rank models by its real strength is the key to Neural Arc...
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Curriculum Learning for Deep Generative Models with Clustering
Training generative models like generative adversarial networks (GANs) a...
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Deep Exemplarbased Video Colorization
This paper presents the first endtoend network for exemplarbased vide...
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LIA: Latently Invertible Autoencoder with Adversarial Learning
Deep generative models play an increasingly important role in machine le...
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Multiobjects Generation with Amortized Structural Regularization
Deep generative models (DGMs) have shown promise in image generation. Ho...
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Learning Semantic Vector Representations of Source Code via a Siamese Neural Network
The abundance of opensource code, coupled with the success of recent ad...
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Estimation of CrossSectional Dependence in Large Panels
Accurate estimation for extent of crosssectional dependence in large pan...
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Deep Hierarchical Reinforcement Learning Based Recommendations via Multigoals Abstraction
The recommender system is an important form of intelligent application, ...
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A Matrixinmatrix Neural Network for Image Super Resolution
In recent years, deep learning methods have achieved impressive results ...
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Artificial Intelligence in Intelligent Tutoring Robots: A Systematic Review and Design Guidelines
This study provides a systematic review of the recent advances in design...
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Function Space Particle Optimization for Bayesian Neural Networks
While Bayesian neural networks (BNNs) have drawn increasing attention, t...
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Bo Zhang
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Professor of Department of Computer Science and Technology at Tsinghua University