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08/10/2023
From CNN to Transformer: A Review of Medical Image Segmentation Models
Medical image segmentation is an important step in medical image analysi...
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07/15/2023
A Graph-Prediction-Based Approach for Debiasing Underreported Data
We present a novel Graph-based debiasing Algorithm for Underreported Dat...
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06/20/2023
Deep graph kernel point processes
Point process models are widely used to analyze asynchronous events occu...
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05/16/2023
Transfer Causal Learning: Causal Effect Estimation with Knowledge Transfer
A novel problem of improving causal effect estimation accuracy with the ...
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02/15/2023
Variable Selection for Kernel Two-Sample Tests
We consider the variable selection problem for two-sample tests, aiming ...
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01/26/2023
Causal Structural Learning from Time Series: A Convex Optimization Approach
Structural learning, which aims to learn directed acyclic graphs (DAGs) ...
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01/26/2023
Causal Graph Discovery from Self and Mutually Exciting Time Series
We present a generalized linear structural causal model, coupled with a ...
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11/29/2022
Novelty Detection for Election Fraud: A Case Study with Agent-Based Simulation Data
In this paper, we propose a robust election simulation model and indepen...
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11/28/2022
Online Kernel CUSUM for Change-Point Detection
We develop an online kernel Cumulative Sum (CUSUM) procedure, which cons...
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11/22/2022
Online Detection Of Supply Chain Network Disruptions Using Sequential Change-Point Detection for Hawkes Processes
In this paper, we attempt to detect an inflection or change-point result...
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11/21/2022
Spatio-temporal point processes with deep non-stationary kernels
Point process data are becoming ubiquitous in modern applications, such ...
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11/14/2022
Tides Need STEMMED: A Locally Operating Spatio-Temporal Mutually Exciting Point Process with Dynamic Network for Improving Opioid Overdose Death Prediction
We develop a Spatio-TEMporal Mutually Exciting point process with Dynami...
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10/31/2022
Training Neural Networks for Sequential Change-point Detection
Detecting an abrupt distributional shift of the data stream, known as ch...
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10/31/2022
Data-Adaptive Symmetric CUSUM for Sequential Change Detection
Detecting change points sequentially in a streaming setting, especially ...
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10/26/2022
Optimal Sub-sampling to Boost Power of Kernel Sequential Change-point Detection
We present a novel scheme to boost detection power for kernel maximum me...
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10/24/2022
Online Critical-State Detection of Sepsis Among ICU Patients using Jensen-Shannon Divergence
Sepsis is a severe medical condition caused by a dysregulated host respo...
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10/11/2022
Sequential change-point detection: Computation versus statistical performance
Change-point detection studies the problem of detecting the changes in t...
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09/09/2022
Granger Causal Chain Discovery for Sepsis-Associated Derangements via Multivariate Hawkes Processes
Modern health care systems are conducting continuous, automated surveill...
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07/07/2022
Neural Stein critics with staged L^2-regularization
Learning to differentiate model distributions from observed data is a fu...
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06/14/2022
Window-Limited CUSUM for Sequential Change Detection
We study the parametric online changepoint detection problem, where the ...
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06/02/2022
Invertible Neural Networks for Graph Prediction
In this work, we address conditional generation using deep invertible ne...
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05/04/2022
A Manifold Two-Sample Test Study: Integral Probability Metric with Neural Networks
Two-sample tests are important areas aiming to determine whether two col...
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03/08/2022
PERCEPT: a new online change-point detection method using topological data analysis
Topological data analysis (TDA) provides a set of data analysis tools fo...
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02/17/2022
Training neural networks using monotone variational inequality
Despite the vast empirical success of neural networks, theoretical under...
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02/09/2022
A Data-Driven Approach to Robust Hypothesis Testing Using Sinkhorn Uncertainty Sets
Hypothesis testing for small-sample scenarios is a practically important...
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02/08/2022
Police Text Analysis: Topic Modeling and Spatial Relative Density Estimation
We analyze a large corpus of police incident narrative documents in unde...
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02/08/2022
Learning Sinkhorn divergences for supervised change point detection
Many modern applications require detecting change points in complex sequ...
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09/24/2021
Sinkhorn Distributionally Robust Optimization
We study distributionally robust optimization with Sinkorn distance – a ...
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09/20/2021
A spatio-temporal analysis for power grid resilience to extreme weather
In recent years, extreme weather events frequently cause large-scale pow...
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09/18/2021
Non-stationary spatio-temporal point process modeling for high-resolution COVID-19 data
Most COVID-19 studies commonly report figures of the overall infection a...
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08/30/2021
Multi-Resolution Spatio-Temporal Prediction with Application to Wind Power Generation
This paper proposes a spatio-temporal model for wind speed prediction wh...
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08/29/2021
Survival Analysis with Graph-Based Regularization for Predictors
We study the variable selection problem in survival analysis to identify...
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06/20/2021
Neural Spectral Marked Point Processes
Self- and mutually-exciting point processes are popular models in machin...
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06/06/2021
Neural Tangent Kernel Maximum Mean Discrepancy
We present a novel neural network Maximum Mean Discrepancy (MMD) statist...
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06/04/2021
Inferring Granger Causality from Irregularly Sampled Time Series
Continuous, automated surveillance systems that incorporate machine lear...
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05/31/2021
Early Detection of COVID-19 Hotspots Using Spatio-Temporal Data
Recently, the Centers for Disease Control and Prevention (CDC) has worke...
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05/29/2021
Robust Hypothesis Testing with Wasserstein Uncertainty Sets
We consider a data-driven robust hypothesis test where the optimal test ...
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05/25/2021
Conformal Anomaly Detection on Spatio-Temporal Observations with Missing Data
We develop a distribution-free, unsupervised anomaly detection method ca...
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05/07/2021
Kernel MMD Two-Sample Tests for Manifold Data
We present a study of kernel MMD two-sample test statistics in the manif...
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04/18/2021
Harvesting data revolution for transmission electron microscopy (TEM) using signal processing
TEM (Transmission Electron Microscopy) is a powerful tool for imaging ma...
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04/09/2021
Sequential (Quickest) Change Detection: Classical Results and New Directions
Online detection of changes in stochastic systems, referred to as sequen...
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03/30/2021
Data-Driven Optimization for Police Zone Design
We present a data-driven optimization framework for redesigning police p...
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02/27/2021
Online High-Dimensional Change-Point Detection using Topological Data Analysis
Topological Data Analysis (TDA) is a rapidly growing field, which studie...
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02/12/2021
Two-sample Test with Kernel Projected Wasserstein Distance
We develop a kernel projected Wasserstein distance for the two-sample te...
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02/11/2021
Optimality of Graph Scanning Statistic for Online Community Detection
Sequential change-point detection for graphs is a fundamental problem fo...
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02/10/2021
Sequential change-point detection for mutually exciting point processes over networks
We present a new CUSUM procedure for sequentially detecting change-point...
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02/09/2021
Balanced Districting on Grid Graphs with Provable Compactness and Contiguity
Given a graph G = (V,E) with vertex weights w(v) and a desired number of...
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01/27/2021
Solar Radiation Anomaly Events Modeling Using Spatial-Temporal Mutually Interactive Processes
Modeling and predicting solar events, in particular, the solar ramping e...
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01/26/2021
Inferring serial correlation with dynamic backgrounds
Sequential data with serial correlation and an unknown, unstructured, an...
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01/05/2021
