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ORCIDDaniel B. Neill
Person information
- affiliation: New York University, Courant Institute / Wagner School / Center for Urban Science and Progress, NY, USA
- affiliation (2006 - 2018): University of Pittsburgh, Department of Biomedical Informatics, PA, USA
- affiliation (PhD 2006): Carnegie Mellon University, Pittsburgh, PA, USA
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2020 – today
- 2023
[j18]Charles A. Pehlivanian, Daniel B. Neill
:
Efficient Optimization of Partition Scan Statistics via the Consecutive Partitions Property. J. Comput. Graph. Stat. 32(2): 712-729 (2023)- [j17]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: 133:1-133:57 (2023) - [c25]Pavan Ravishankar, Qingyu Mo, Edward McFowland III, Daniel B. Neill:
Provable Detection of Propagating Sampling Bias in Prediction Models. AAAI 2023: 9562-9569 - [c24]Katie Rosman, Daniel B. Neill:
Detecting Anomalous Networks of Opioid Prescribers and Dispensers in Prescription Drug Data. AAAI 2023: 14470-14477 - [c23]Konstantin Klemmer, Nathan S. Safir, Daniel B. Neill:
Positional Encoder Graph Neural Networks for Geographic Data. AISTATS 2023: 1379-1389 - [i15]Pavan Ravishankar, Qingyu Mo, Edward McFowland III, Daniel B. Neill:
Provable Detection of Propagating Sampling Bias in Prediction Models. CoRR abs/2302.06752 (2023) - [i14]Neil Menghani, Edward McFowland III, Daniel B. Neill:
Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness. CoRR abs/2306.11181 (2023) - [i13]Kate S. Boxer, Edward McFowland III, Daniel B. Neill:
Auditing Predictive Models for Intersectional Biases. CoRR abs/2306.13064 (2023) - 2022
- [c22]Chunpai Wang, Daniel B. Neill, Feng Chen:
Calibrated Nonparametric Scan Statistics for Anomalous Pattern Detection in Graphs. AAAI 2022: 4201-4209 - [c21]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: 4523-4531 - [i12]Chunpai Wang, Daniel B. Neill, Feng Chen:
Calibrated Nonparametric Scan Statistics for Anomalous Pattern Detection in Graphs. CoRR abs/2206.12786 (2022) - 2021
- [j16]Dylan J. Fitzpatrick, Yun Ni, Daniel B. Neill:
Support vector subset scan for spatial pattern detection. Comput. Stat. Data Anal. 157: 107149 (2021) - [c20]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 - [c19]Konstantin Klemmer, Daniel B. Neill:
Auxiliary-task learning for geographic data with autoregressive embeddings. SIGSPATIAL/GIS 2021: 141-144 - [i11]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 abs/2109.15044 (2021) - [i10]Konstantin Klemmer, Nathan Safir, Daniel B. Neill:
Positional Encoder Graph Neural Networks for Geographic Data. CoRR abs/2111.10144 (2021) - 2020
- [j15]Amr Magdy, Xun Zhou, Daniel B. Neill:
Guest Editorial: Special Issue on Analytics for Local Events and News. GeoInformatica 24(2): 267-268 (2020) - [i9]Konstantin Klemmer, Daniel B. Neill:
SXL: Spatially explicit learning of geographic processes with auxiliary tasks. CoRR abs/2006.10461 (2020) - [i8]Dylan J. Fitzpatrick, Wilpen L. Gorr, Daniel B. Neill:
Policing Chronic and Temporary Hot Spots of Violent Crime: A Controlled Field Experiment. CoRR abs/2011.06019 (2020)
2010 – 2019
- 2019
- [j14]William Herlands, Daniel B. Neill, Hannes Nickisch, Andrew Gordon Wilson:
Change Surfaces for Expressive Multidimensional Changepoints and Counterfactual Prediction. J. Mach. Learn. Res. 20: 99:1-99:51 (2019) - [c18]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: 359-368 - 2018
- [j13]Maria De-Arteaga, William Herlands, Daniel B. Neill, Artur Dubrawski:
Machine Learning for the Developing World. ACM Trans. Manag. Inf. Syst. 9(2): 9:1-9:14 (2018) - [c17]William Herlands, Edward McFowland, Andrew Gordon Wilson, Daniel B. Neill:
Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data. AISTATS 2018: 425-434 - [c16]William Herlands, Edward McFowland III, Andrew Gordon Wilson, Daniel B. Neill:
Automated Local Regression Discontinuity Design Discovery. KDD 2018: 1512-1520 - [r3]Skyler Speakman, Sriram Somanchi, Edward McFowland III, Daniel B. Neill:
Disease Surveillance: Case Study. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018 - [i7]William Herlands, Edward McFowland III, Andrew Gordon Wilson, Daniel B. Neill:
Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data. CoRR abs/1804.01466 (2018) - [i6]William Herlands, Daniel B. Neill, Hannes Nickisch, Andrew Gordon Wilson:
Change Surfaces for Expressive Multidimensional Changepoints and Counterfactual Prediction. CoRR abs/1810.11861 (2018) - [i5]Konstantin Klemmer, Daniel B. Neill, Stephen A. Jarvis:
Modeling Rape Reporting Delays Using Spatial, Temporal and Social Features. CoRR abs/1811.03939 (2018) - 2017
- [j12]Sriram Somanchi, Daniel B. Neill:
Graph Structure Learning from Unlabeled Data for Early Outbreak Detection. IEEE Intell. Syst. 32(2): 80-84 (2017) - [r2]Daniel B. Neill:
Subset Scanning for Event and Pattern Detection. Encyclopedia of GIS 2017: 2218-2228 - [i4]Sriram Somanchi, Daniel B. Neill:
Graph Structure Learning from Unlabeled Data for Event Detection. CoRR abs/1701.01470 (2017) - [i3]Daniel B. Neill, William Herlands:
Machine Learning for Drug Overdose Surveillance. CoRR abs/1710.02458 (2017) - 2016
- [j11]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): 22:1-22:23 (2016) - [c15]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: 1013-1021 - [i2]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 abs/1602.04393 (2016) - [i1]Zhe Zhang, Daniel B. Neill:
Identifying Significant Predictive Bias in Classifiers. CoRR abs/1611.08292 (2016) - 2015
- [j10]Feng Chen, Daniel B. Neill:
Human Rights Event Detection from Heterogeneous Social Media Graphs. Big Data 3(1): 34-40 (2015) - [j9]Daniel Gartner, Rainer Kolisch, Daniel B. Neill, Rema Padman:
Machine Learning Approaches for Early DRG Classification and Resource Allocation. INFORMS J. Comput. 27(4): 718-734 (2015) - [c14]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: 607-616 - 2014
- [c13]Feng Chen, Daniel B. Neill:
Non-parametric scan statistics for event detection and forecasting in heterogeneous social media graphs. KDD 2014: 1166-1175 - [e1]Xiaolong Zheng, Daniel Zeng, Hsinchun Chen, Yong Zhang, Chunxiao Xing, Daniel B. Neill:
Smart Health - International Conference, ICSH 2014, Beijing, China, July 10-11, 2014. Proceedings. Lecture Notes in Computer Science 8549, Springer 2014, ISBN 978-3-319-08415-2 [contents] - [r1]Skyler Speakman, Sriram Somanchi, Edward McFowland, Daniel B. Neill:
Disease Surveillance, Case Study. Encyclopedia of Social Network Analysis and Mining 2014: 380-385 - 2013
- [j8]Daniel B. Neill:
Using Artificial Intelligence to Improve Hospital Inpatient Care. IEEE Intell. Syst. 28(2): 92-95 (2013) - [j7]Edward McFowland, Skyler Speakman, Daniel B. Neill:
Fast generalized subset scan for anomalous pattern detection. J. Mach. Learn. Res. 14(1): 1533-1561 (2013) - [c12]Skyler Speakman, Yating Zhang, Daniel B. Neill:
Dynamic Pattern Detection with Temporal Consistency and Connectivity Constraints. ICDM 2013: 697-706 - 2012
- [j6]Daniel B. Neill:
New Directions in Artificial Intelligence for Public Health Surveillance. IEEE Intell. Syst. 27(1): 56-59 (2012) - [j5]Christopher A. Harle, Daniel B. Neill, Rema Padman:
Information Visualization for Chronic Disease Risk Assessment. IEEE Intell. Syst. 27(6): 81-85 (2012) - 2011
- [j4]Sharique Hasan, George T. Duncan, Daniel B. Neill, Rema Padman:
Automatic detection of omissions in medication lists. J. Am. Medical Informatics Assoc. 18(4): 449-458 (2011) - [j3]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): 21-30 (2011) - [c11]Kan Shao, Yandong Liu, Daniel B. Neill:
A Generalized Fast Subset Sums Framework for Bayesian Event Detection. ICDM 2011: 617-625 - 2010
- [j2]Xia Jiang, Daniel B. Neill, Gregory F. Cooper:
A Bayesian network model for spatial event surveillance. Int. J. Approx. Reason. 51(2): 224-239 (2010) - [j1]Daniel B. Neill, Gregory F. Cooper:
A multivariate Bayesian scan statistic for early event detection and characterization. Mach. Learn. 79(3): 261-282 (2010)
2000 – 2009
- 2009
- [c10]Xia Jiang, Gregory F. Cooper, Daniel B. Neill:
Generalized AMOC Curves For Evaluation and Improvement of Event Surveillance. AMIA 2009 - [c9]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: 495 - 2008
- [c8]Sharique Hasan, George T. Duncan, Daniel B. Neill, Rema Padman:
Towards a Collaborative Filtering Approach to Medication Reconciliation. AMIA 2008 - [c7]Kaustav Das, Jeff G. Schneider, Daniel B. Neill:
Anomaly pattern detection in categorical datasets. KDD 2008: 169-176 - 2005
- [c6]Daniel B. Neill, Andrew W. Moore, Maheshkumar Sabhnani, Kenny Daniel:
Detection of emerging space-time clusters. KDD 2005: 218-227 - [c5]Daniel B. Neill, Andrew W. Moore, Gregory F. Cooper:
A Bayesian Spatial Scan Statistic. NIPS 2005: 1003-1010 - 2004
- [c4]Daniel B. Neill, Andrew W. Moore:
Rapid detection of significant spatial clusters. KDD 2004: 256-265 - [c3]Daniel B. Neill, Andrew W. Moore, Francisco Pereira, Tom M. Mitchell:
Detecting Significant Multidimensional Spatial Clusters. NIPS 2004: 969-976 - 2003
- [c2]Daniel B. Neill, Andrew W. Moore:
A Fast Multi-Resolution Method for Detection of Significant Spatial Disease Clusters. NIPS 2003: 651-658 - [c1]Daniel B. Neill:
Cooperation and coordination in the turn-taking dilemma. TARK 2003: 231-244
Coauthor Index
aka: Edward McFowland III
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