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06/14/2023
Uncertainty-Aware Robust Learning on Noisy Graphs
Graph neural networks have shown impressive capabilities in solving vari...
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05/25/2023
Counterfactual Generative Models for Time-Varying Treatments
Estimating average causal effects is a common practice to test new treat...
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05/21/2023
Conditional Generative Modeling is All You Need for Marked Temporal Point Processes
Recent advancements in generative modeling have made it possible to gene...
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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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06/20/2021
Neural Spectral Marked Point Processes
Self- and mutually-exciting point processes are popular models in machin...
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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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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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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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02/09/2021
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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09/15/2020
High-resolution Spatio-temporal Model for County-level COVID-19 Activity in the U.S
We present an interpretable high-resolution spatio-temporal model to est...
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06/16/2020
Goodness-of-Fit Test for Self-Exciting Processes
Recently there have been many research efforts in developing generative ...
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06/07/2020
Distributionally Robust k-Nearest Neighbors for Few-Shot Learning
Learning a robust classifier from a few samples remains a key challenge ...
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05/15/2020
Spatio-Temporal Point Processes with Attention for Traffic Congestion Event Modeling
We present a novel framework for modeling traffic congestion events over...
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04/20/2020
Data-Driven Optimization for Police Beat Design in South Fulton, Georgia
We redesign the police patrol beat in South Fulton, Georgia, in collabor...
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02/17/2020
Deep Attention Spatio-Temporal Point Processes
We present a novel attention-based sequential model for mutually depende...
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10/21/2019
Adversarial Anomaly Detection for Marked Spatio-Temporal Streaming Data
Spatio-temporal event data are becoming increasingly available in a wide...
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06/13/2019
Reinforcement Learning of Spatio-Temporal Point Processes
Spatio-temporal event data is ubiquitous in various applications, such a...
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02/01/2019
Crime Linkage Detection by Spatial-Temporal-Textual Point Processes
Crimes emerge out of complex interactions of behaviors and situations; t...
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11/12/2018
Learning Temporal Point Processes via Reinforcement Learning
Social goods, such as healthcare, smart city, and information networks, ...
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06/15/2018
Crime Event Embedding with Unsupervised Feature Selection
We present a novel event embedding algorithm for crime data that can joi...
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10/28/2017