b'Wei Pan'

research

∙ 09/18/2023

Discovery and inference of a causal network with hidden confounding

This article proposes a novel causal discovery and inference method call...

0 Li Chen, et al. ∙

research

∙ 09/02/2023

Few shot font generation via transferring similarity guided global style and quantization local style

Automatic few-shot font generation (AFFG), aiming at generating new font...

0 Wei Pan, et al. ∙

research

∙ 05/16/2023

Reinforcement Learning for Safe Robot Control using Control Lyapunov Barrier Functions

Reinforcement learning (RL) exhibits impressive performance when managin...

0 Desong Du, et al. ∙

research

∙ 05/06/2023

Weighted Point Cloud Normal Estimation

Existing normal estimation methods for point clouds are often less robus...

3 Weijia Wang, et al. ∙

research

∙ 02/26/2023

Sim-and-Real Reinforcement Learning for Manipulation: A Consensus-based Approach

Sim-and-real training is a promising alternative to sim-to-real training...

0 Wenxing Liu, et al. ∙

research

∙ 02/07/2023

Nonlinear Causal Discovery with Confounders

This article introduces a causal discovery method to learn nonlinear rel...

0 Chunlin Li, et al. ∙

research

∙ 11/18/2022

Data-Adaptive Discriminative Feature Localization with Statistically Guaranteed Interpretation

In explainable artificial intelligence, discriminative feature localizat...

0 Ben Dai, et al. ∙

research

∙ 10/04/2022

Flexible Instrumental Variable Models With Bayesian Additive Regression Trees

Methods utilizing instrumental variables have been a fundamental statist...

0 Charles Spanbauer, et al. ∙

research

∙ 09/19/2022

Inference of nonlinear causal effects with GWAS summary data

Large-scale genome-wide association studies (GWAS) have offered an excit...

0 Ben Dai, et al. ∙

research

∙ 07/15/2022

Theoretical analysis and numerical approximation for the stochastic thermal quasi-geostrophic model

This paper investigates the mathematical properties of a stochastic vers...

0 Dan Crisan, et al. ∙

research

∙ 06/01/2022

Bayesian Learning to Discover Mathematical Operations in Governing Equations of Dynamic Systems

Discovering governing equations from data is critical for diverse scient...

0 Hongpeng Zhou, et al. ∙

research

∙ 03/11/2022

AI-enabled Automatic Multimodal Fusion of Cone-Beam CT and Intraoral Scans for Intelligent 3D Tooth-Bone Reconstruction and Clinical Applications

A critical step in virtual dental treatment planning is to accurately de...

0 Jin Hao, et al. ∙

research

∙ 02/22/2022

A pathwise parameterisation for stochastic transport

In this work we set the stage for a new probabilistic pathwise approach ...

0 Oana Lang, et al. ∙

research

∙ 01/05/2022

Towards Uniform Point Distribution in Feature-preserving Point Cloud Filtering

As a popular representation of 3D data, point cloud may contain noise an...

2 Shuaijun Chen, et al. ∙

research

∙ 12/18/2021

Model-Based Safe Reinforcement Learning with Time-Varying State and Control Constraints: An Application to Intelligent Vehicles

Recently, barrier function-based safe reinforcement learning (RL) with t...

8 Xinglong Zhang, et al. ∙

research

∙ 10/07/2021

Inference for a Large Directed Graphical Model with Interventions

Inference of directed relations given some unspecified interventions, th...

0 Chunlin Li, et al. ∙

research

∙ 10/06/2021

Two-level monotonic multistage recommender systems

A recommender system learns to predict the user-specific preference or i...

0 Ben Dai, et al. ∙

research

∙ 07/27/2021

Sparse Bayesian Deep Learning for Dynamic System Identification

This paper proposes a sparse Bayesian treatment of deep neural networks ...

0 Hongpeng Zhou, et al. ∙

research

∙ 07/25/2021

Reinforcement Learning Compensated Extended Kalman Filter for Attitude Estimation

Inertial measurement units are widely used in different fields to estima...

0 Yujie Tang, et al. ∙

research

∙ 04/19/2021

Probabilistic Mixture-of-Experts for Efficient Deep Reinforcement Learning

Deep reinforcement learning (DRL) has successfully solved various proble...

0 Jie Ren, et al. ∙

research

∙ 03/03/2021

Reinforcement Learning for Orientation Estimation Using Inertial Sensors with Performance Guarantee

This paper presents a deep reinforcement learning (DRL) algorithm for or...

0 Liang Hu, et al. ∙

research

∙ 03/02/2021

Significance tests of feature relevance for a blackbox learner

An exciting recent development is the uptake of deep learning in many sc...

0 Ben Dai, et al. ∙

research

∙ 11/13/2020

Reinforcement Learning Control of Constrained Dynamic Systems with Uniformly Ultimate Boundedness Stability Guarantee

Reinforcement learning (RL) is promising for complicated stochastic nonl...

10 Minghao Han, et al. ∙

research

∙ 10/26/2020

Lyapunov-Based Reinforcement Learning State Estimator

In this paper, we consider the state estimation problem for nonlinear st...

0 Liang Hu, et al. ∙

research

∙ 10/18/2020

Social-VRNN: One-Shot Multi-modal Trajectory Prediction for Interacting Pedestrians

Prediction of human motions is key for safe navigation of autonomous rob...

0 Bruno Brito, et al. ∙

research

∙ 10/13/2020

Penalized model-based clustering of fMRI data

Functional magnetic resonance imaging (fMRI) data have become increasing...

7 Andrew DiLernia, et al. ∙

research

∙ 09/20/2020

Lyapunov-Based Reinforcement Learning for Decentralized Multi-Agent Control

Decentralized multi-agent control has broad applications, ranging from m...

0 Qingrui Zhang, et al. ∙

research

∙ 08/26/2020

Assessing Impact of Unobserved Confounders with Sensitivity Index Probabilities through Pseudo-Experiments

Unobserved confounders are a long-standing issue in causal inference usi...

0 Beilin Jia, et al. ∙

research

∙ 08/17/2020

Model-Reference Reinforcement Learning for Collision-Free Tracking Control of Autonomous Surface Vehicles

This paper presents a novel model-reference reinforcement learning algor...

0 Qingrui Zhang, et al. ∙

research

∙ 08/08/2020

Towards Lossless Binary Convolutional Neural Networks Using Piecewise Approximation

Binary Convolutional Neural Networks (CNNs) can significantly reduce the...

0 Baozhou Zhu Zaid Al-Ars, et al. ∙

research

∙ 08/04/2020

Segmentation Based Mesh Denoising

Feature-preserving mesh denoising has received noticeable attention rece...

0 Chaofan Dai, et al. ∙

research

∙ 04/29/2020

Actor-Critic Reinforcement Learning for Control with Stability Guarantee

Deep Reinforcement Learning (DRL) has achieved impressive performance in...

0 Minghao Han, et al. ∙

research

∙ 03/30/2020

Model-Reference Reinforcement Learning Control of Autonomous Surface Vehicles with Uncertainties

This paper presents a novel model-reference reinforcement learning contr...

0 Qingrui Zhang, et al. ∙

research

∙ 03/20/2020

Gaussian Curvature Filter on 3D Mesh

Minimizing Gaussian curvature of meshes is fundamentally important for o...

0 Wenming Tang, et al. ∙

research

∙ 11/15/2019

A Sparse Bayesian Deep Learning Approach for Identification of Cascaded Tanks Benchmark

Nonlinear system identification is important with a wide range of applic...

0 Hongpeng Zhou, et al. ∙

research

∙ 11/07/2019

H_∞ Model-free Reinforcement Learning with Robust Stability Guarantee

Reinforcement learning is showing great potentials in robotics applicati...

0 Minghao Han, et al. ∙

research

∙ 11/07/2019

H_inf Model-free Reinforcement Learning with Robust Stability Guarantee

Reinforcement learning is showing great potentials in robotics applicati...

0 Minghao Han, et al. ∙

research

∙ 10/01/2019

Data assimilation for a quasi-geostrophic model with circulation-preserving stochastic transport noise

This paper contains the latest installment of the authors' project on de...

0 Colin Cotter, et al. ∙

research

∙ 07/27/2019

A Particle Filter for Stochastic Advection by Lie Transport (SALT): A case study for the damped and forced incompressible 2D Euler equation

In this work, we apply a particle filter with three additional procedure...

0 Colin Cotter, et al. ∙

research

∙ 05/13/2019

BayesNAS: A Bayesian Approach for Neural Architecture Search

One-Shot Neural Architecture Search (NAS) is a promising method to signi...

9 Hongpeng Zhou, et al. ∙

research

∙ 05/12/2019

HLO: Half-kernel Laplacian Operator for Surface Smoothing

This paper presents a simple yet effective method for feature-preserving...

0 Wei Pan, et al. ∙

research

∙ 01/26/2019

Probabilistic Recursive Reasoning for Multi-Agent Reinforcement Learning

Humans are capable of attributing latent mental contents such as beliefs...

12 Ying Wen, et al. ∙

research

∙ 10/01/2018

Data-driven Discovery of Cyber-Physical Systems

Cyber-physical systems (CPSs) embed software into the physical world. Th...

0 Xiuchuan Tang, et al. ∙

research

∙ 09/02/2018

Asymptotically Independent U-Statistics in High-Dimensional Testing

Many high-dimensional hypothesis tests aim to globally examine marginal ...

0 Yinqiu He, et al. ∙

research

∙ 11/30/2017

Towards Accurate Binary Convolutional Neural Network

We introduce a novel scheme to train binary convolutional neural network...

0 Xiaofan Lin, et al. ∙

research

∙ 09/30/2017

Enabling Quality Control for Entity Resolution: A Human and Machine Cooperation Framework

Even though many machine algorithms have been proposed for entity resolu...

0 Zhaoqiang Chen, et al. ∙

research

∙ 10/15/2016

Mixed Neural Network Approach for Temporal Sleep Stage Classification

This paper proposes a practical approach to addressing limitations posed...

0 Hao Dong, et al. ∙

research

∙ 08/05/2016

Human collective intelligence as distributed Bayesian inference

Collective intelligence is believed to underly the remarkable success of...

0 Peter M Krafft, et al. ∙

research

∙ 06/23/2016

DropNeuron: Simplifying the Structure of Deep Neural Networks

Deep learning using multi-layer neural networks (NNs) architecture manif...

0 Wei Pan, et al. ∙

research

∙ 02/21/2008

Penalized model-based clustering with cluster-specific diagonal covariance matrices and grouped variables

Clustering analysis is one of the most widely used statistical tools in ...

0 Benhuai Xie, et al. ∙

Wei Pan

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