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09/18/2023
Discovery and inference of a causal network with hidden confounding
This article proposes a novel causal discovery and inference method call...
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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...
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05/16/2023
Reinforcement Learning for Safe Robot Control using Control Lyapunov Barrier Functions
Reinforcement learning (RL) exhibits impressive performance when managin...
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05/06/2023
Weighted Point Cloud Normal Estimation
Existing normal estimation methods for point clouds are often less robus...
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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...
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02/07/2023
Nonlinear Causal Discovery with Confounders
This article introduces a causal discovery method to learn nonlinear rel...
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11/18/2022
Data-Adaptive Discriminative Feature Localization with Statistically Guaranteed Interpretation
In explainable artificial intelligence, discriminative feature localizat...
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10/04/2022
Flexible Instrumental Variable Models With Bayesian Additive Regression Trees
Methods utilizing instrumental variables have been a fundamental statist...
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09/19/2022
Inference of nonlinear causal effects with GWAS summary data
Large-scale genome-wide association studies (GWAS) have offered an excit...
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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...
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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...
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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...
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02/22/2022
A pathwise parameterisation for stochastic transport
In this work we set the stage for a new probabilistic pathwise approach ...
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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...
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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...
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10/07/2021
Inference for a Large Directed Graphical Model with Interventions
Inference of directed relations given some unspecified interventions, th...
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10/06/2021
Two-level monotonic multistage recommender systems
A recommender system learns to predict the user-specific preference or i...
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07/27/2021
Sparse Bayesian Deep Learning for Dynamic System Identification
This paper proposes a sparse Bayesian treatment of deep neural networks ...
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07/25/2021
Reinforcement Learning Compensated Extended Kalman Filter for Attitude Estimation
Inertial measurement units are widely used in different fields to estima...
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04/19/2021
Probabilistic Mixture-of-Experts for Efficient Deep Reinforcement Learning
Deep reinforcement learning (DRL) has successfully solved various proble...
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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...
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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...
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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...
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10/26/2020
Lyapunov-Based Reinforcement Learning State Estimator
In this paper, we consider the state estimation problem for nonlinear st...
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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...
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10/13/2020
Penalized model-based clustering of fMRI data
Functional magnetic resonance imaging (fMRI) data have become increasing...
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09/20/2020
Lyapunov-Based Reinforcement Learning for Decentralized Multi-Agent Control
Decentralized multi-agent control has broad applications, ranging from m...
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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...
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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...
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08/08/2020
Towards Lossless Binary Convolutional Neural Networks Using Piecewise Approximation
Binary Convolutional Neural Networks (CNNs) can significantly reduce the...
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08/04/2020
Segmentation Based Mesh Denoising
Feature-preserving mesh denoising has received noticeable attention rece...
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04/29/2020
Actor-Critic Reinforcement Learning for Control with Stability Guarantee
Deep Reinforcement Learning (DRL) has achieved impressive performance in...
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03/30/2020
Model-Reference Reinforcement Learning Control of Autonomous Surface Vehicles with Uncertainties
This paper presents a novel model-reference reinforcement learning contr...
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03/20/2020
Gaussian Curvature Filter on 3D Mesh
Minimizing Gaussian curvature of meshes is fundamentally important for o...
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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...
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11/07/2019
H_∞ Model-free Reinforcement Learning with Robust Stability Guarantee
Reinforcement learning is showing great potentials in robotics applicati...
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11/07/2019
H_inf Model-free Reinforcement Learning with Robust Stability Guarantee
Reinforcement learning is showing great potentials in robotics applicati...
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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...
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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...
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05/13/2019
BayesNAS: A Bayesian Approach for Neural Architecture Search
One-Shot Neural Architecture Search (NAS) is a promising method to signi...
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05/12/2019
HLO: Half-kernel Laplacian Operator for Surface Smoothing
This paper presents a simple yet effective method for feature-preserving...
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01/26/2019
Probabilistic Recursive Reasoning for Multi-Agent Reinforcement Learning
Humans are capable of attributing latent mental contents such as beliefs...
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10/01/2018
Data-driven Discovery of Cyber-Physical Systems
Cyber-physical systems (CPSs) embed software into the physical world. Th...
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09/02/2018
Asymptotically Independent U-Statistics in High-Dimensional Testing
Many high-dimensional hypothesis tests aim to globally examine marginal ...
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11/30/2017
Towards Accurate Binary Convolutional Neural Network
We introduce a novel scheme to train binary convolutional neural network...
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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...
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10/15/2016
Mixed Neural Network Approach for Temporal Sleep Stage Classification
This paper proposes a practical approach to addressing limitations posed...
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08/05/2016
Human collective intelligence as distributed Bayesian inference
Collective intelligence is believed to underly the remarkable success of...
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06/23/2016
DropNeuron: Simplifying the Structure of Deep Neural Networks
Deep learning using multi-layer neural networks (NNs) architecture manif...
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02/21/2008
