B. Aditya Prakash

Orcid: 0000-0002-3252-455X

Affiliations:
  • Georgia Institute of Technology, USA
  • Carnegie Mellon University, Pittsburgh, USA (PhD 2012)


According to our database1, B. Aditya Prakash authored at least 120 papers between 2007 and 2024.

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Bibliography

2024
Learning Graph Structures and Uncertainty for Accurate and Calibrated Time-series Forecasting.
CoRR, 2024

TSI-Bench: Benchmarking Time Series Imputation.
CoRR, 2024

Time-MMD: A New Multi-Domain Multimodal Dataset for Time Series Analysis.
CoRR, 2024

H<sup>2</sup>ABM: Heterogeneous Agent-based Model on Hypergraphs to Capture Group Interactions.
Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

epiDAMIK 2024: The 7th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Large Scale Hierarchical Industrial Demand Time-Series Forecasting incorporating Sparsity.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

A Review of Graph Neural Networks in Epidemic Modeling.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensation.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
Empirical networks for localized COVID-19 interventions using WiFi infrastructure at university campuses.
Frontiers Digit. Health, March, 2023

Large Pre-trained time series models for cross-domain Time series analysis tasks.
CoRR, 2023

PEMS: Pre-trained Epidemic Time-series Models.
CoRR, 2023

Performative Time-Series Forecasting.
CoRR, 2023

DF2: Distribution-Free Decision-Focused Learning.
CoRR, 2023

Uncertainty Quantification in Deep Learning.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

When Rigidity Hurts: Soft Consistency Regularization for Probabilistic Hierarchical Time Series Forecasting.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

epiDAMIK 6.0: The 6th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Autoregressive Diffusion Model for Graph Generation.
Proceedings of the International Conference on Machine Learning, 2023

Differentiable Agent-based Epidemiology.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

EINNs: Epidemiologically-Informed Neural Networks.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Detecting Sources of Healthcare Associated Infections.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Differentiable Agent-based Epidemiology.
CoRR, 2022

Data-Centric Epidemic Forecasting: A Survey.
CoRR, 2022

PROFHIT: Probabilistic Robust Forecasting for Hierarchical Time-series.
CoRR, 2022

CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

End-to-end Stochastic Optimization with Energy-based Model.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Epidemic Forecasting with a Data-Centric Lens.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

epiDAMIK 5.0: The 5th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Provable Sensor Sets for Epidemic Detection over Networks with Minimum Delay.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Incorporating Expert Guidance in Epidemic Forecasting.
CoRR, 2021

When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

The 4th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery (epiDAMIK 4.0 @ KDD2021).
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Actionable Insights in Urban Multivariate Time-series.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Efficient Contingency Analysis in Power Systems via Network Trigger Nodes.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

DeepCOVID: An Operational Deep Learning-driven Framework for Explainable Real-time COVID-19 Forecasting.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Cut-n-Reveal: Time Series Segmentations with Explanations.
ACM Trans. Intell. Syst. Technol., 2020

NetReAct: Interactive Learning for Network Summarization.
CoRR, 2020

Mapping Network States using Connectivity Queries.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

Designing Effective and Practical Interventions to Contain Epidemics.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019
Tracking and analyzing dynamics of news-cycles during global pandemics: a historical perspective.
SIGKDD Explor., 2019

Fast and near-optimal monitoring for healthcare acquired infection outbreaks.
PLoS Comput. Biol., 2019

Data-driven efficient network and surveillance-based immunization.
Knowl. Inf. Syst., 2019

Joint Post and Link-level Influence Modeling on Social Media.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

EpiDeep: Exploiting Embeddings for Epidemic Forecasting.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

2018
Automatic Segmentation of Dynamic Network Sequences with Node Labels.
IEEE Trans. Knowl. Data Eng., 2018

Propagation-Based Temporal Network Summarization.
IEEE Trans. Knowl. Data Eng., 2018

Efficiently summarizing attributed diffusion networks.
Data Min. Knowl. Discov., 2018

Mining E-Commerce Query Relations using Customer Interaction Networks.
Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Near-Optimal Mapping of Network States using Probes.
Proceedings of the 2018 SIAM International Conference on Data Mining, 2018

SIGNet: Scalable Embeddings for Signed Networks.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

Sub2Vec: Feature Learning for Subgraphs.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

DeepDiffuse: Predicting the 'Who' and 'When' in Cascades.
Proceedings of the IEEE International Conference on Data Mining, 2018

NetGist: Learning to Generate Task-Based Network Summaries.
Proceedings of the IEEE International Conference on Data Mining, 2018

Automatic Segmentation of Data Sequences.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Nonlinear Dynamics of Information Diffusion in Social Networks.
ACM Trans. Web, 2017

Understanding the Relationship between Human Behavior and Susceptibility to Cyber Attacks: A Data-Driven Approach.
ACM Trans. Intell. Syst. Technol., 2017

Distributed Representation of Subgraphs.
CoRR, 2017

Detecting Large Reshare Cascades in Social Networks.
Proceedings of the 26th International Conference on World Wide Web, 2017

MeiKe: Influence-based Communities in Networks.
Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Condensing Temporal Networks using Propagation.
Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Data-Driven Immunization.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Distributed Representations of Subgraphs.
Proceedings of the 2017 IEEE International Conference on Data Mining Workshops, 2017

HotSpots: Failure Cascades on Heterogeneous Critical Infrastructure Networks.
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

SnapNETS: Automatic Segmentation of Network Sequences with Node Labels.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Near-Optimal Algorithms for Controlling Propagation at Group Scale on Networks.
IEEE Trans. Knowl. Data Eng., 2016

Node Immunization on Large Graphs: Theory and Algorithms.
IEEE Trans. Knowl. Data Eng., 2016

Eigen-Optimization on Large Graphs by Edge Manipulation.
ACM Trans. Knowl. Discov. Data, 2016

Current and Future Challenges in Mining Large Networks: Report on the Second SDM Workshop on Mining Networks and Graphs.
SIGKDD Explor., 2016

Prediction Using Propagation: From Flu Trends to Cybersecurity.
IEEE Intell. Syst., 2016

Syndromic surveillance of Flu on Twitter using weakly supervised temporal topic models.
Data Min. Knowl. Discov., 2016

Forecasting the Flu: Designing Social Network Sensors for Epidemics.
CoRR, 2016

Ensemble Models for Data-driven Prediction of Malware Infections.
Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, 2016

Unstable Communities in Network Ensembles.
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Reconstructing an Epidemic Over Time.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Leveraging Propagation for Data Mining: Models, Algorithms and Applications.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Segmenting Sequences of Node-Labeled Graphs.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2016

URBAN-NET: A network-based infrastructure monitoring and analysis system for emergency management and public safety.
Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

2015
Graph Mining for Cyber Security.
Proceedings of the Cyber Warfare - Building the Scientific Foundation, 2015

Data-Aware Vaccine Allocation Over Large Networks.
ACM Trans. Knowl. Discov. Data, 2015

Hidden Hazards: Finding Missing Nodes in Large Graph Epidemics.
Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

Approximation Algorithms for Reducing the Spectral Radius to Control Epidemic Spread.
Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

Controlling Propagation at Group Scale on Networks.
Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

Mining Unstable Communities from Network Ensembles.
Proceedings of the IEEE International Conference on Data Mining Workshop, 2015

The Global Cyber-Vulnerability Report
Terrorism, Security, and Computation, Springer, ISBN: 978-3-319-25760-0, 2015

2014
SharkFin: Spatio-temporal mining of software adoption and penetration.
Soc. Netw. Anal. Min., 2014

Efficiently spotting the starting points of an epidemic in a large graph.
Knowl. Inf. Syst., 2014

DAVA: Distributing Vaccines over Networks under Prior Information.
Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

Fast influence-based coarsening for large networks.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Modeling mass protest adoption in social network communities using geometric brownian motion.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Flu Gone Viral: Syndromic Surveillance of Flu on Twitter Using Temporal Topic Models.
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

Scalable Vaccine Distribution in Large Graphs given Uncertain Data.
Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014

SansText: Classifying temporal topic dynamics of Twitter cascades without tweet text.
Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2014

2013
Competing Memes Propagation on Networks: A Network Science Perspective.
IEEE J. Sel. Areas Commun., 2013

Fractional Immunization in Networks.
Proceedings of the 13th SIAM International Conference on Data Mining, 2013

Patterns amongst Competing Task Frequencies: Super-Linearities, and the Almond-DG Model.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2013

Smartphone viruses propagation on heterogeneous composite networks.
Proceedings of the 2nd IEEE Network Science Workshop, 2013

Spatio-temporal mining of software adoption & penetration.
Proceedings of the Advances in Social Networks Analysis and Mining 2013, 2013

2012
Understanding and Managing Cascades on Large Graphs.
Proc. VLDB Endow., 2012

Threshold conditions for arbitrary cascade models on arbitrary networks.
Knowl. Inf. Syst., 2012

Propagation and immunization in large networks.
XRDS, 2012

Competing memes propagation on networks: a case study of composite networks.
Comput. Commun. Rev., 2012

Winner takes all: competing viruses or ideas on fair-play networks.
Proceedings of the 21st World Wide Web Conference 2012, 2012

Rise and fall patterns of information diffusion: model and implications.
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Interacting viruses in networks: can both survive?
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Spotting Culprits in Epidemics: How Many and Which Ones?
Proceedings of the 12th IEEE International Conference on Data Mining, 2012

Gelling, and melting, large graphs by edge manipulation.
Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

2011
Epidemic Spread in Mobile Ad Hoc Networks: Determining the Tipping Point.
Proceedings of the NETWORKING 2011, 2011

Time Series Clustering: Complex is Simpler!
Proceedings of the 28th International Conference on Machine Learning, 2011

2010
Parsimonious Linear Fingerprinting for Time Series.
Proc. VLDB Endow., 2010

Virus Propagation on Time-Varying Networks: Theory and Immunization Algorithms.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Metric forensics: a multi-level approach for mining volatile graphs.
Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

On the Vulnerability of Large Graphs.
Proceedings of the ICDM 2010, 2010

2009
FRAPP: a framework for high-accuracy privacy-preserving mining.
Data Min. Knowl. Discov., 2009

BGP-lens: patterns and anomalies in internet routing updates.
Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

EigenSpokes: Surprising Patterns and Scalable Community Chipping in Large Graphs.
Proceedings of the ICDM Workshops 2009, 2009

2007
Complex Group-By Queries for XML.
Proceedings of the 23rd International Conference on Data Engineering, 2007


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