research
∙
07/20/2023
Learning Dense UV Completion for Human Mesh Recovery
Human mesh reconstruction from a single image is challenging in the pres...
share
research
∙
07/17/2023
Complexity Matters: Rethinking the Latent Space for Generative Modeling
In generative modeling, numerous successful approaches leverage a low-di...
research
∙
05/05/2023
Random Smoothing Regularization in Kernel Gradient Descent Learning
Random smoothing data augmentation is a unique form of regularization th...
research
∙
03/24/2023
Zolly: Zoom Focal Length Correctly for Perspective-Distorted Human Mesh Reconstruction
As it is hard to calibrate single-view RGB images in the wild, existing ...
research
∙
01/28/2023
Deciphering the Projection Head: Representation Evaluation Self-supervised Learning
Self-supervised learning (SSL) aims to learn intrinsic features without ...
research
∙
01/25/2023
mcGP: mesh-clustered Gaussian process emulator for partial differential equation systems
Partial differential equations (PDEs) have become an essential tool for ...
research
∙
12/07/2022
An automated approach to extracting positive and negative clinical research results
Failure is common in clinical trials since the successful failures prese...
research
∙
11/25/2022
Soft BPR Loss for Dynamic Hard Negative Sampling in Recommender Systems
In recommender systems, leveraging Graph Neural Networks (GNNs) to formu...
research
∙
03/16/2022
WegFormer: Transformers for Weakly Supervised Semantic Segmentation
Although convolutional neural networks (CNNs) have achieved remarkable p...
research
∙
01/10/2022
Differentiable and Scalable Generative Adversarial Models for Data Imputation
Data imputation has been extensively explored to solve the missing data ...
research
∙
01/09/2022
Smooth Nested Simulation: Bridging Cubic and Square Root Convergence Rates in High Dimensions
Nested simulation concerns estimating functionals of a conditional expec...
research
∙
01/05/2022
Functional-Input Gaussian Processes with Applications to Inverse Scattering Problems
Surrogate modeling based on Gaussian processes (GPs) has received increa...
research
∙
12/07/2021
Understanding Square Loss in Training Overparametrized Neural Network Classifiers
Deep learning has achieved many breakthroughs in modern classification t...
research
∙
04/20/2021
Convergence of Gaussian process regression: Optimality, robustness, and relationship with kernel ridge regression
In this work, we investigate Gaussian process regression used to recover...
research
∙
01/21/2021
Trans2Seg: Transparent Object Segmentation with Transformer
This work presents a new fine-grained transparent object segmentation da...
research
∙
11/21/2020
Neural Network Gaussian Process Considering Input Uncertainty for Composite Structures Assembly
Developing machine learning enabled smart manufacturing is promising for...
research
∙
07/06/2020
Regularization Matters: A Nonparametric Perspective on Overparametrized Neural Network
Overparametrized neural networks trained by gradient descent (GD) can pr...
research
∙
05/07/2020
Scene Text Image Super-Resolution in the Wild
Low-resolution text images are often seen in natural scenes such as docu...
research
∙
05/04/2020
Reduced Rank Multivariate Kernel Ridge Regression
In the multivariate regression, also referred to as multi-task learning ...
research
∙
04/21/2020
Imbalanced Sparse Canonical Correlation Analysis
Classical canonical correlation analysis (CCA) requires matrices to be l...
research
∙
03/31/2020
Segmenting Transparent Objects in the Wild
Transparent objects such as windows and bottles made by glass widely exi...
research
∙
02/04/2020
Uncertainty Quantification for Bayesian Optimization
Bayesian optimization is a class of global optimization techniques. It r...
research
∙
02/04/2020
Gaussian Processes with Input Location Error and Applications to the Composite Parts Assembly Process
In this paper, we investigate Gaussian process regression with input loc...
research
∙
02/04/2020
On the Inference of Applying Gaussian Process Modeling to a Deterministic Function
The Gaussian process modeling is a standard tool for building emulators ...
research
∙
11/13/2019
Kriging prediction with isotropic Matérn correlations: robustness and experimental design
We investigate the prediction performance of the kriging predictors. We ...
research
∙
11/04/2019
PGU-net+: Progressive Growing of U-net+ for Automated Cervical Nuclei Segmentation
Automated cervical nucleus segmentation based on deep learning can effec...
research
∙
09/16/2019
TextSR: Content-Aware Text Super-Resolution Guided by Recognition
Scene text recognition has witnessed rapid development with the advance ...
research
∙
09/13/2019
A Double Penalty Model for Interpretability
Modern statistical learning techniques have often emphasized prediction ...
research
∙
08/16/2019
Efficient and Accurate Arbitrary-Shaped Text Detection with Pixel Aggregation Network
Scene text detection, an important step of scene text reading systems, h...
research
∙
04/19/2019
Automated Segmentation of Pulmonary Lobes using Coordination-Guided Deep Neural Networks
The identification of pulmonary lobes is of great importance in disease ...
research
∙
11/17/2017
AI Challenger : A Large-scale Dataset for Going Deeper in Image Understanding
Significant progress has been achieved in Computer Vision by leveraging ...
research
∙
10/18/2017
