Intelligent virus detection on mobile devices. - Deepak Venugopal; Guoning Hu; Nicoleta Roman (PST, 2006)

An efficient signature representation and matching method for mobile devices. - Deepak Venugopal (WICON, 2006)

A Malware Signature Extraction and Detection Method Applied to Mobile Networks. - Guoning Hu; Deepak Venugopal (IPCCC, 2007)

Efficient signature based malware detection on mobile devices. - Deepak Venugopal; Guoning Hu (Mob. Inf. Syst., 2008)

Advances in Lifted Importance Sampling. - Vibhav Gogate; Abhay Kumar Jha; Deepak Venugopal (AAAI, 2012)

On Lifting the Gibbs Sampling Algorithm. - Deepak Venugopal; Vibhav Gogate (NIPS, 2012)

GiSS: Combining Gibbs Sampling and SampleSearch for Inference in Mixed Probabilistic and Deterministic Graphical Models. - Deepak Venugopal; Vibhav Gogate (AAAI, 2013)

Dynamic Blocking and Collapsing for Gibbs Sampling. - Deepak Venugopal; Vibhav Gogate (UAI, 2013)

Evidence-Based Clustering for Scalable Inference in Markov Logic. - Deepak Venugopal; Vibhav Gogate (StarAI@AAAI, 2014)

Lifted MAP Inference for Markov Logic Networks. - Somdeb Sarkhel; Deepak Venugopal; Parag Singla; Vibhav Gogate (AISTATS, 2014)

Relieving the Computational Bottleneck: Joint Inference for Event Extraction with High-Dimensional Features. - Deepak Venugopal; Chen Chen 004; Vibhav Gogate; Vincent Ng 001 (EMNLP, 2014)

An Integer Polynomial Programming Based Framework for Lifted MAP Inference. - Somdeb Sarkhel; Deepak Venugopal; Parag Singla; Vibhav Gogate (NIPS, 2014)

Scaling-up Importance Sampling for Markov Logic Networks. - Deepak Venugopal; Vibhav Gogate (NIPS, 2014)

Scaling-Up Inference in Markov Logic. - Deepak Venugopal (AAAI, 2015)

Just Count the Satisfied Groundings: Scalable Local-Search and Sampling Based Inference in MLNs. - Deepak Venugopal; Somdeb Sarkhel; Vibhav Gogate (AAAI, 2015)

Scalable Training of Markov Logic Networks Using Approximate Counting. - Somdeb Sarkhel; Deepak Venugopal; Tuan Anh Pham; Parag Singla; Vibhav Gogate (AAAI, 2016)

Joint Inference for Event Coreference Resolution. - Jing Lu; Deepak Venugopal; Vibhav Gogate; Vincent Ng 001 (COLING, 2016)

Joint Inference for Mode Identification in Tutorial Dialogues. - Deepak Venugopal; Vasile Rus (COLING, 2016)

Non-parametric Domain Approximation for Scalable Gibbs Sampling in MLNs. - Deepak Venugopal; Somdeb Sarkhel; Kyle Cherry (UAI, 2016)

Efficient Inference for Untied MLNs. - Somdeb Sarkhel; Deepak Venugopal; Nicholas Ruozzi; Vibhav Gogate (IJCAI, 2017)

Adaptive blocked Gibbs sampling for inference in probabilistic graphical models. - Mohammad Maminur Islam; Mohammad Khan Al Farabi; Deepak Venugopal (IJCNN, 2017)

Advances in Inference Methods for Markov Logic Networks. - Deepak Venugopal (IEEE Intell. Informatics Bull., 2017)

Learning Mixtures of MLNs. - Mohammad Maminur Islam; Somdeb Sarkhel; Deepak Venugopal (AAAI, 2018)

Efficient Weight Learning in High-Dimensional Untied MLNs. - Khan Mohammad Al Farabi; Somdeb Sarkhel; Deepak Venugopal (AISTATS, 2018)

Scaling up Inference in MLNs with Spark. - Mohammad Maminur Islam; Khan Mohammad Al Farabi; Somdeb Sarkhel; Deepak Venugopal (IEEE BigData, 2018)

Fine-Grained Crime Prediction in an Urban Neighborhood. - Christopher Kent; Deepak Venugopal (ISC2, 2018)

Detecting Review Manipulation on Online Platforms with Hierarchical Supervised Learning. - Naveen Kumar; Deepak Venugopal; Liangfei Qiu; Subodha Kumar (J. Manag. Inf. Syst., 2018)

On Lifted Inference Using Neural Embeddings. - Mohammad Maminur Islam; Somdeb Sarkhel; Deepak Venugopal (AAAI, 2019)

Adaptive Rao-Blackwellisation in Gibbs Sampling for Probabilistic Graphical Models. - Craig Kelly; Somdeb Sarkhel; Deepak Venugopal (AISTATS, 2019)

Comparative Analysis of ML Classifiers for Network Intrusion Detection. - Ahmed M. Mahfouz; Deepak Venugopal; Sajjan G. Shiva (ICICT (2), 2019)

Fine-Grained Explanations Using Markov Logic. - Khan Mohammad Al Farabi; Somdeb Sarkhel; Sanorita Dey; Deepak Venugopal (ECML/PKDD (2), 2019)

DDoS Intrusion Detection Through Machine Learning Ensemble. - Saikat Das; Ahmed M. Mahfouz; Deepak Venugopal; Sajjan G. Shiva (QRS Companion, 2019)

Detecting Anomalous Online Reviewers: An Unsupervised Approach Using Mixture Models. - Naveen Kumar; Deepak Venugopal; Liangfei Qiu; Subodha Kumar (J. Manag. Inf. Syst., 2019)

Augmenting Deep Learning with Relational Knowledge from Markov Logic Networks. - Mohammad Maminur Islam; Somdeb Sarkhel; Deepak Venugopal (IEEE BigData, 2020)

Empirical Evaluation of the Ensemble Framework for Feature Selection in DDoS Attack. - Saikat Das; Deepak Venugopal; Sajjan G. Shiva; Frederick T. Sheldon (CSCloud/EdgeCom, 2020)

CIDMP: Completely Interpretable Detection of Malaria Parasite in Red Blood Cells using Lower-dimensional Feature Space. - Anik Khan; Kishor Datta Gupta; Deepak Venugopal; Nirman Kumar (IJCNN, 2020)

Taxonomy and Survey of Interpretable Machine Learning Method. - Saikat Das; Namita Agarwal; Deepak Venugopal; Frederick T. Sheldon; Sajjan G. Shiva (SSCI, 2020)

Ensemble Classifiers for Network Intrusion Detection Using a Novel Network Attack Dataset. - Ahmed M. Mahfouz; Abdullah Abuhussein; Deepak Venugopal; Sajjan G. Shiva (Future Internet, 2020)

Interpretable Explanations for Probabilistic Inference in Markov Logic. - Khan Mohammad Al Farabi; Somdeb Sarkhel; Sanorita Dey; Deepak Venugopal (IEEE BigData, 2021)

Contrastive Learning in Neural Tensor Networks using Asymmetric Examples. - Mohammad Maminur Islam; Somdeb Sarkhel; Deepak Venugopal (IEEE BigData, 2021)

The Nature of Achievement Goal Motivation Profiles: Exploring Situational Motivation in An Algebra-Focused Intelligent Tutoring System. - Leigh M. Harrell-Williams; Christian Mueller; Stephen Fancsali; Steven Ritter 001; Xiaofei Zhang 002; Deepak Venugopal (EDM (Workshops), 2021)

The Learner Data Institute - Conceptualization: A Progress Report. - Vasile Rus; Stephen E. Fancsali; Philip I. Pavlik Jr.; Deepak Venugopal; Arthur C. Graesser; Steven Ritter 001; Dale Bowman; The L. D. I. Team (EDM (Workshops), 2021)

Student Strategy Prediction using a Neuro-Symbolic Approach. - Anup Shakya; Vasile Rus; Deepak Venugopal (EDM, 2021)

Neuro-Symbolic Models: A Scalable, Explainable Framework for Strategy Discovery from Big Edu-Data. - Deepak Venugopal; Vasile Rus; Anup Shakya (EDM (Workshops), 2021)

An Information-theoretic approach to dimensionality reduction in data science. - Sambriddhi Mainali; Max H. Garzon; Deepak Venugopal; Kalidas Jana; Ching-Chi Yang; Nirman Kumar; Dale Bowman; Lih-Yuan Deng (Int. J. Data Sci. Anal., 2021)

Evaluating Captioning Models using Markov Logic Networks. - Monika Shah; Somdeb Sarkhel; Deepak Venugopal (IEEE Big Data, 2022)

Question Modifiers in Visual Question Answering. - William Britton; Somdeb Sarkhel; Deepak Venugopal (LREC, 2022)

Verifying Relational Explanations: A Probabilistic Approach. - Abisha Thapa Magar; Anup Shakya; Somdeb Sarkhel; Deepak Venugopal (IEEE Big Data, 2023)

Scalable and Equitable Math Problem Solving Strategy Prediction in Big Educational Data. - Anup Shakya; Vasile Rus; Deepak Venugopal (EDM, 2023)

On the Verification of Embeddings with Hybrid Markov Logic. - Anup Shakya; Abisha Thapa Magar; Somdeb Sarkhel; Deepak Venugopal (ICDM, 2023)

On the verification of Embeddings using Hybrid Markov Logic. - Anup Shakya; Abisha Thapa Magar; Somdeb Sarkhel; Deepak Venugopal (CoRR, 2023)

Disentangling Fine-Tuning from Pre-Training in Visual Captioning with Hybrid Markov Logic. - Monika Shah; Somdeb Sarkhel; Deepak Venugopal (IEEE Big Data, 2024)

Learning Representations for Math Strategies using BERT. - Abisha Thapa Magar; Stephen E. Fancsali; Vasile Rus; April Murphy; Steven Ritter 001; Deepak Venugopal (L@S, 2024)

Mastery Guided Non-parametric Clustering to Scale-up Strategy Prediction. - Anup Shakya; Vasile Rus; Deepak Venugopal (CoRR, 2024)

Analyzing Strategies in MATHia with BERT. - Abisha Thapa Magar; Stephen E. Fancsali; Vasile Rus; April Murphy; Steven Ritter 001; Deepak Venugopal (AIED (6), 2025)

"Can A Language Model Represent Math Strategies?": Learning Math Strategies from Big Data using BERT. - Abisha Thapa Magar; Anup Shakya; Stephen E. Fancsali; Vasile Rus; April Murphy; Steven Ritter 001; Deepak Venugopal (LAK, 2025)

Reparameterizing Hybrid Markov Logic Networks to handle Covariate-Shift in Representations. - Anup Shakya; Abisha Thapa Magar; Somdeb Sarkhel; Deepak Venugopal (UAI, 2025)

On Explaining Visual Captioning with Hybrid Markov Logic Networks. - Monika Shah; Somdeb Sarkhel; Deepak Venugopal (CoRR, 2025)

Analyzing the Sensitivity of Vision Language Models in Visual Question Answering. - Monika Shah; Sudarshan Balaji; Somdeb Sarkhel; Sanorita Dey; Deepak Venugopal (CoRR, 2025)