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07/03/2023
OpenClinicalAI: An Open and Dynamic Model for Alzheimer's Disease Diagnosis
Although Alzheimer's disease (AD) cannot be reversed or cured, timely di...
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07/03/2023
OpenAPMax: Abnormal Patterns-based Model for Real-World Alzheimer's Disease Diagnosis
Alzheimer's disease (AD) cannot be reversed, but early diagnosis will si...
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04/21/2023
Picking Up Quantization Steps for Compressed Image Classification
The sensitivity of deep neural networks to compressed images hinders the...
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03/09/2023
3D Video Loops from Asynchronous Input
Looping videos are short video clips that can be looped endlessly withou...
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08/18/2022
A Decorrelating and Debiasing Approach to Simultaneous Inference for High-Dimensional Confounded Models
Motivated by the simultaneous association analysis with the presence of ...
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08/04/2022
Tree stick-breaking priors for covariate-dependent mixture models
Stick-breaking priors are often adopted in Bayesian nonparametric mixtur...
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07/05/2022
Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing
Big data processing at the production scale presents a highly complex en...
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07/01/2022
Neural Parameterization for Dynamic Human Head Editing
Implicit radiance functions emerged as a powerful scene representation f...
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03/20/2022
TVConv: Efficient Translation Variant Convolution for Layout-aware Visual Processing
As convolution has empowered many smart applications, dynamic convolutio...
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01/25/2022
NAPA: Neighborhood-Assisted and Posterior-Adjusted Two-sample Inference
Two-sample multiple testing problems of sparse spatial data are frequent...
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11/29/2021
Deblur-NeRF: Neural Radiance Fields from Blurry Images
Neural Radiance Field (NeRF) has gained considerable attention recently ...
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09/11/2021
Microbiome subcommunity learning with logistic-tree normal latent Dirichlet allocation
Mixed-membership (MM) models such as Latent Dirichlet Allocation (LDA) h...
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09/09/2021
OpenClinicalAI: enabling AI to diagnose diseases in real-world clinical settings
This paper quantitatively reveals the state-of-the-art and state-of-the-...
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08/19/2021
Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency Domain
Recently, the generalization behavior of Convolutional Neural Networks (...
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06/29/2021
Logistic-tree normal model for microbiome compositions
We introduce a probabilistic model, called the "logistic-tree normal" (L...
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02/14/2021
Distillation based Multi-task Learning: A Candidate Generation Model for Improving Reading Duration
In feeds recommendation, the first step is candidate generation. Most of...
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01/26/2021
Tree boosting for learning probability measures
Learning probability measures based on an i.i.d. sample is a fundamental...
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11/05/2020
Hidden Markov Pólya trees for high-dimensional distributions
The Pólya tree (PT) process is a general-purpose Bayesian nonparametric ...
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08/02/2020
Dirichlet-tree multinomial mixtures for clustering microbiome compositions
A common routine in microbiome research is to identify reproducible patt...
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02/11/2020
Privacy-preserving collaborative machine learning on genomic data using TensorFlow
Machine learning (ML) methods have been widely used in genomic studies. ...
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01/17/2020
Coarsened mixtures of hierarchical skew normal kernels for flow cytometry analyses
Flow cytometry (FCM) is the standard multi-parameter assay used to measu...
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12/11/2019
CARP: Compression through Adaptive Recursive Partitioning for Multi-dimensional Images
Fast and effective image compression for multi-dimensional images has be...
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07/27/2019
G-flocking: Flocking Model Optimization based on Genetic Framework
Flocking model has been widely used to control robotic swarm. However, w...
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03/18/2019
POI Semantic Model with a Deep Convolutional Structure
When using the electronic map, POI retrieval is the initial and importan...
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06/18/2018
MultiFIT: A Multivariate Multiscale Framework for Independence Tests
We present a framework for testing independence between two random vecto...
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06/18/2018
MultiFIT: Multivariate Multiscale Framework for Independence Tests
We present a framework for testing independence between two random vecto...
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12/13/2017
Bayesian graphical compositional regression for microbiome data
An important task in microbiome studies is to test the existence of and ...
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11/02/2017
Partition mixture of 1D wavelets for multi-dimensional data
Traditional statistical wavelet analysis that carries out modeling and i...
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04/17/2017
Mixture modeling on related samples by ψ-stick breaking and kernel perturbation
There has been great interest recently in applying nonparametric kernel ...
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02/12/2016
