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09/23/2022
Understanding Open-Set Recognition by Jacobian Norm of Representation
In contrast to conventional closed-set recognition, open-set recognition...
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08/04/2022
Customs Import Declaration Datasets
Given the huge volume of cross-border flows, effective and efficient con...
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07/14/2022
A Spatio-Temporal Dirichlet Process Mixture Model for Coronavirus Disease-19
Understanding the spatio-temporal patterns of the coronavirus disease 20...
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12/16/2021
DProST: 6-DoF Object Pose Estimation Using Space Carving and Dynamic Projective Spatial Transformer
Predicting the pose of an object is a core computer vision task. Most de...
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12/12/2020
Periocular in the Wild Embedding Learning with Cross-Modal Consistent Knowledge Distillation
Periocular biometric, or peripheral area of ocular, is a collaborative a...
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11/26/2020
A Scalable Partitioned Approach to Model Massive Nonstationary Non-Gaussian Spatial Datasets
Nonstationary non-Gaussian spatial data are common in many disciplines, ...
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08/06/2020
Bayesian Indirect Inference for Models with Intractable Normalizing Functions
Inference for doubly intractable distributions is challenging because th...
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06/24/2020
Bayesian Shrinkage for Functional Network Models with Intractable Normalizing Constants
Longitudinal network models are widely used to study the time-varying re...
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03/03/2020
Compact Surjective Encoding Autoencoder for Unsupervised Novelty Detection
In unsupervised novelty detection, a model is trained solely on the in-c...
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11/17/2019
Bayesian Model Selection for Ultrahigh-Dimensional Doubly-Intractable Distributions with an Application to Network Psychometrics
Doubly intractable distributions commonly arise in many complex statisti...
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10/22/2019
Reduced-dimensional Monte Carlo Maximum Likelihood for Latent Gaussian Random Field Models
Monte Carlo maximum likelihood (MCML) provides an elegant approach to fi...
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03/02/2019
PuVAE: A Variational Autoencoder to Purify Adversarial Examples
Deep neural networks are widely used and exhibit excellent performance i...
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11/17/2018
Stacking-Based Deep Neural Network: Deep Analytic Network for Pattern Classification
Stacking-based deep neural network (S-DNN) is aggregated with pluralitie...
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06/20/2018
