Daniel B. Neill

Publication Activity (10 Years)

Years Active: 2003-2023
Publications (10 Years): 37

Top Topics

Gaussian Process

Pattern Detection

Top Venues

J. Mach. Learn. Res.

Publications

Charles A. Pehlivanian, Daniel B. Neill
Efficient Optimization of Partition Scan Statistics via the Consecutive Partitions Property. J. Comput. Graph. Stat. 32 (2) (2023)
Konstantin Klemmer, Nathan S. Safir, Daniel B. Neill
Positional Encoder Graph Neural Networks for Geographic Data. AISTATS (2023)
Katie Rosman, Daniel B. Neill
Detecting Anomalous Networks of Opioid Prescribers and Dispensers in Prescription Drug Data. AAAI (2023)
Pavan Ravishankar, Qingyu Mo, Edward McFowland III, Daniel B. Neill
Provable Detection of Propagating Sampling Bias in Prediction Models. AAAI (2023)
Neil Menghani, Edward McFowland III, Daniel B. Neill
Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness. CoRR (2023)
Pavan Ravishankar, Qingyu Mo, Edward McFowland III, Daniel B. Neill
Provable Detection of Propagating Sampling Bias in Prediction Models. CoRR (2023)
Kate S. Boxer, Edward McFowland III, Daniel B. Neill
Auditing Predictive Models for Intersectional Biases. CoRR (2023)
Benjamin Jakubowski, Sriram Somanchi, Edward McFowland III, Daniel B. Neill
Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators. J. Mach. Learn. Res. 24 (2023)
Konstantin Klemmer, Tianlin Xu, Beatrice Acciaio, Daniel B. Neill
SPATE-GAN: Improved Generative Modeling of Dynamic Spatio-Temporal Patterns with an Autoregressive Embedding Loss. AAAI (2022)
Chunpai Wang, Daniel B. Neill, Feng Chen
Calibrated Nonparametric Scan Statistics for Anomalous Pattern Detection in Graphs. CoRR (2022)
Chunpai Wang, Daniel B. Neill, Feng Chen
Calibrated Nonparametric Scan Statistics for Anomalous Pattern Detection in Graphs. AAAI (2022)
Dylan J. Fitzpatrick, Yun Ni, Daniel B. Neill
Support vector subset scan for spatial pattern detection. Comput. Stat. Data Anal. 157 (2021)
Skyler Speakman, Girmaw Abebe Tadesse, Victor Akinwande, William Ogallo, Claire-Helene Mershon, Nosa Orobaton, Daniel B. Neill
Automatic Stratification of Tabular Health Data. AMIA (2021)
Konstantin Klemmer, Tianlin Xu, Beatrice Acciaio, Daniel B. Neill
SPATE-GAN: Improved Generative Modeling of Dynamic Spatio-Temporal Patterns with an Autoregressive Embedding Loss. CoRR (2021)
Konstantin Klemmer, Nathan Safir, Daniel B. Neill
Positional Encoder Graph Neural Networks for Geographic Data. CoRR (2021)
Konstantin Klemmer, Daniel B. Neill
Auxiliary-task learning for geographic data with autoregressive embeddings. SIGSPATIAL/GIS (2021)
Amr Magdy, Xun Zhou, Daniel B. Neill
Guest Editorial: Special Issue on Analytics for Local Events and News. GeoInformatica 24 (2) (2020)
Konstantin Klemmer, Daniel B. Neill
SXL: Spatially explicit learning of geographic processes with auxiliary tasks. CoRR (2020)
Dylan J. Fitzpatrick, Wilpen L. Gorr, Daniel B. Neill
Policing Chronic and Temporary Hot Spots of Violent Crime: A Controlled Field Experiment. CoRR (2020)
Roberto C. S. N. P. Souza, Renato M. Assunção, Daniel B. Neill, Wagner Meira Jr.
Detecting Spatial Clusters of Disease Infection Risk Using Sparsely Sampled Social Media Mobility Patterns. SIGSPATIAL/GIS (2019)
William Herlands, Daniel B. Neill, Hannes Nickisch, Andrew Gordon Wilson
Change Surfaces for Expressive Multidimensional Changepoints and Counterfactual Prediction. J. Mach. Learn. Res. 20 (2019)
William Herlands, Edward McFowland III, Andrew Gordon Wilson, Daniel B. Neill
Automated Local Regression Discontinuity Design Discovery. KDD (2018)
Maria De-Arteaga, William Herlands, Daniel B. Neill, Artur Dubrawski
Machine Learning for the Developing World. ACM Trans. Manag. Inf. Syst. 9 (2) (2018)
William Herlands, Daniel B. Neill, Hannes Nickisch, Andrew Gordon Wilson
Change Surfaces for Expressive Multidimensional Changepoints and Counterfactual Prediction. CoRR (2018)
William Herlands, Edward McFowland III, Andrew Gordon Wilson, Daniel B. Neill
Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data. CoRR (2018)
Konstantin Klemmer, Daniel B. Neill, Stephen A. Jarvis
Modeling Rape Reporting Delays Using Spatial, Temporal and Social Features. CoRR (2018)
William Herlands, Edward McFowland, Andrew Gordon Wilson, Daniel B. Neill
Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data. AISTATS (2018)
Sriram Somanchi, Daniel B. Neill
Graph Structure Learning from Unlabeled Data for Early Outbreak Detection. IEEE Intell. Syst. 32 (2) (2017)
Sriram Somanchi, Daniel B. Neill
Graph Structure Learning from Unlabeled Data for Event Detection. CoRR (2017)
Daniel B. Neill, William Herlands
Machine Learning for Drug Overdose Surveillance. CoRR (2017)
Seth R. Flaxman, Daniel B. Neill, Alexander J. Smola
Gaussian Processes for Independence Tests with Non-iid Data in Causal Inference. ACM Trans. Intell. Syst. Technol. 7 (2) (2016)
Abhinav Maurya, Kenton Murray, Yandong Liu, Chris Dyer, William W. Cohen, Daniel B. Neill
Semantic Scan: Detecting Subtle, Spatially Localized Events in Text Streams. CoRR (2016)
Zhe Zhang, Daniel B. Neill
Identifying Significant Predictive Bias in Classifiers. CoRR (2016)
William Herlands, Andrew Gordon Wilson, Hannes Nickisch, Seth R. Flaxman, Daniel B. Neill, Wilbert Van Panhuis, Eric P. Xing
Scalable Gaussian Processes for Characterizing Multidimensional Change Surfaces. AISTATS (2016)
Feng Chen, Daniel B. Neill
Human Rights Event Detection from Heterogeneous Social Media Graphs. Big Data 3 (1) (2015)
Daniel Gartner, Rainer Kolisch, Daniel B. Neill, Rema Padman
Machine Learning Approaches for Early DRG Classification and Resource Allocation. INFORMS J. Comput. 27 (4) (2015)
Seth R. Flaxman, Andrew Gordon Wilson, Daniel B. Neill, Hannes Nickisch, Alexander J. Smola
Fast Kronecker Inference in Gaussian Processes with non-Gaussian Likelihoods. ICML (2015)
Feng Chen, Daniel B. Neill
Non-parametric scan statistics for event detection and forecasting in heterogeneous social media graphs. KDD (2014)
Skyler Speakman, Yating Zhang, Daniel B. Neill
Dynamic Pattern Detection with Temporal Consistency and Connectivity Constraints. ICDM (2013)
Daniel B. Neill
Using Artificial Intelligence to Improve Hospital Inpatient Care. IEEE Intell. Syst. 28 (2) (2013)
Edward McFowland, Skyler Speakman, Daniel B. Neill
Fast generalized subset scan for anomalous pattern detection. J. Mach. Learn. Res. 14 (1) (2013)
Daniel B. Neill
New Directions in Artificial Intelligence for Public Health Surveillance. IEEE Intell. Syst. 27 (1) (2012)
Christopher A. Harle, Daniel B. Neill, Rema Padman
Information Visualization for Chronic Disease Risk Assessment. IEEE Intell. Syst. 27 (6) (2012)
Kan Shao, Yandong Liu, Daniel B. Neill
A Generalized Fast Subset Sums Framework for Bayesian Event Detection. ICDM (2011)
Sharique Hasan, George T. Duncan, Daniel B. Neill, Rema Padman
Automatic detection of omissions in medication lists. J. Am. Medical Informatics Assoc. 18 (4) (2011)
Daniel P. de Oliveira, Daniel B. Neill, James H. Garrett Jr., Lucio Soibelman
Detection of Patterns in Water Distribution Pipe Breakage Using Spatial Scan Statistics for Point Events in a Physical Network. J. Comput. Civ. Eng. 25 (1) (2011)
Daniel B. Neill, Gregory F. Cooper
A multivariate Bayesian scan statistic for early event detection and characterization. Mach. Learn. 79 (3) (2010)
Xia Jiang, Daniel B. Neill, Gregory F. Cooper
A Bayesian network model for spatial event surveillance. Int. J. Approx. Reason. 51 (2) (2010)
Artur Dubrawski, Maheshkumar Sabhnani, Michael Knight, Michael Baysek, Daniel B. Neill, Saswati Ray, Anna Michalska, Nuwan Waidyanatha
T-Cube Web Interface in support of real-time bio-surveillance program. ICTD (2009)
Xia Jiang, Gregory F. Cooper, Daniel B. Neill
Generalized AMOC Curves For Evaluation and Improvement of Event Surveillance. AMIA (2009)
Kaustav Das, Jeff G. Schneider, Daniel B. Neill
Anomaly pattern detection in categorical datasets. KDD (2008)
Sharique Hasan, George T. Duncan, Daniel B. Neill, Rema Padman
Towards a Collaborative Filtering Approach to Medication Reconciliation. AMIA (2008)
Daniel B. Neill, Andrew W. Moore, Maheshkumar Sabhnani, Kenny Daniel
Detection of emerging space-time clusters. KDD (2005)
Daniel B. Neill, Andrew W. Moore, Gregory F. Cooper
A Bayesian Spatial Scan Statistic. NIPS (2005)
Daniel B. Neill, Andrew W. Moore
Rapid detection of significant spatial clusters. KDD (2004)
Daniel B. Neill, Andrew W. Moore, Francisco Pereira, Tom M. Mitchell
Detecting Significant Multidimensional Spatial Clusters. NIPS (2004)
Daniel B. Neill, Andrew W. Moore
A Fast Multi-Resolution Method for Detection of Significant Spatial Disease Clusters. NIPS (2003)
Daniel B. Neill
Cooperation and coordination in the turn-taking dilemma. TARK (2003)