Deepak Venugopal

67 papers A* 10A 8B 11C 2Journal 15Unranked 21

Year	Rank	Type	Title / Venue / Authors
2026	A	`conf`	Understanding and Modeling Math Strategy Use in Intelligent Tutoring Systems. LAK Abisha Thapa Magar, Asad Uzzaman, Tali Zacks, Stephen Fancsali, Vasile Rus, April Murphy, Ethan Shafran Moltz, Steve Ritter, Deepak Venugopal
2025	A	`conf`	"Can A Language Model Represent Math Strategies?": Learning Math Strategies from Big Data using BERT. LAK Abisha Thapa Magar, Anup Shakya, Stephen E. Fancsali, Vasile Rus, April Murphy, Steven Ritter, Deepak Venugopal
2025	—	`conf`	Analyzing Strategies in MATHia with BERT. AIED (6) Abisha Thapa Magar, Stephen E. Fancsali, Vasile Rus, April Murphy, Steven Ritter, Deepak Venugopal
2025	J	`jnl`	Analyzing the Sensitivity of Vision Language Models in Visual Question Answering. CoRR Monika Shah, Sudarshan Balaji, Somdeb Sarkhel, Sanorita Dey, Deepak Venugopal
2025	J	`jnl`	Disentangling Fine-Tuning from Pre-Training in Visual Captioning with Hybrid Markov Logic. CoRR Monika Shah, Somdeb Sarkhel, Deepak Venugopal
2025	J	`jnl`	On Explaining Visual Captioning with Hybrid Markov Logic Networks. CoRR Monika Shah, Somdeb Sarkhel, Deepak Venugopal
2025	A	`conf`	Reparameterizing Hybrid Markov Logic Networks to handle Covariate-Shift in Representations. UAI Anup Shakya, Abisha Thapa Magar, Somdeb Sarkhel, Deepak Venugopal
2024	B	`conf`	Disentangling Fine-Tuning from Pre-Training in Visual Captioning with Hybrid Markov Logic. IEEE Big Data Monika Shah, Somdeb Sarkhel, Deepak Venugopal
2024	B	`conf`	Learning Representations for Math Strategies using BERT. L@S Abisha Thapa Magar, Stephen E. Fancsali, Vasile Rus, April Murphy, Steven Ritter, Deepak Venugopal
2024	J	`jnl`	Mastery Guided Non-parametric Clustering to Scale-up Strategy Prediction. CoRR Anup Shakya, Vasile Rus, Deepak Venugopal
2024	J	`jnl`	Verifying Relational Explanations: A Probabilistic Approach. CoRR Abisha Thapa Magar, Anup Shakya, Somdeb Sarkhel, Deepak Venugopal
2023	A*	`conf`	On the Verification of Embeddings with Hybrid Markov Logic. ICDM Anup Shakya, Abisha Thapa Magar, Somdeb Sarkhel, Deepak Venugopal
2023	J	`jnl`	On the verification of Embeddings using Hybrid Markov Logic. CoRR Anup Shakya, Abisha Thapa Magar, Somdeb Sarkhel, Deepak Venugopal
2023	B	`conf`	Scalable and Equitable Math Problem Solving Strategy Prediction in Big Educational Data. EDM Anup Shakya, Vasile Rus, Deepak Venugopal
2023	J	`jnl`	Scalable and Equitable Math Problem Solving Strategy Prediction in Big Educational Data. CoRR Anup Shakya, Vasile Rus, Deepak Venugopal
2023	B	`conf`	Verifying Relational Explanations: A Probabilistic Approach. IEEE Big Data Abisha Thapa Magar, Anup Shakya, Somdeb Sarkhel, Deepak Venugopal
2022	B	`conf`	Evaluating Captioning Models using Markov Logic Networks. IEEE Big Data Monika Shah, Somdeb Sarkhel, Deepak Venugopal
2022	B	`conf`	Question Modifiers in Visual Question Answering. LREC William Britton, Somdeb Sarkhel, Deepak Venugopal
2021	J	`jnl`	An Information-theoretic approach to dimensionality reduction in data science. Int. J. Data Sci. Anal. Sambriddhi Mainali, Max H. Garzon, Deepak Venugopal, Kalidas Jana, Ching-Chi Yang, Nirman Kumar, Dale Bowman, Lih-Yuan Deng
2021	—	`conf`	Contrastive Learning in Neural Tensor Networks using Asymmetric Examples. IEEE BigData Mohammad Maminur Islam, Somdeb Sarkhel, Deepak Venugopal
2021	—	`conf`	Interpretable Explanations for Probabilistic Inference in Markov Logic. IEEE BigData Khan Mohammad Al Farabi, Somdeb Sarkhel, Sanorita Dey, Deepak Venugopal
2021	—	`conf`	Neuro-Symbolic Models: A Scalable, Explainable Framework for Strategy Discovery from Big Edu-Data. EDM (Workshops) Deepak Venugopal, Vasile Rus, Anup Shakya
2021	B	`conf`	Student Strategy Prediction using a Neuro-Symbolic Approach. EDM Anup Shakya, Vasile Rus, Deepak Venugopal
2021	—	`conf`	The Learner Data Institute - Conceptualization: A Progress Report. EDM (Workshops) Vasile Rus, Stephen E. Fancsali, Philip I. Pavlik Jr., Deepak Venugopal, Arthur C. Graesser, Steven Ritter, Dale Bowman, The LDI Team
2021	—	`conf`	The Nature of Achievement Goal Motivation Profiles: Exploring Situational Motivation in An Algebra-Focused Intelligent Tutoring System. EDM (Workshops) Leigh M. Harrell-Williams, Christian Mueller, Stephen Fancsali, Steven Ritter, Xiaofei Zhang, Deepak Venugopal
2020	—	`conf`	Augmenting Deep Learning with Relational Knowledge from Markov Logic Networks. IEEE BigData Mohammad Maminur Islam, Somdeb Sarkhel, Deepak Venugopal
2020	B	`conf`	CIDMP: Completely Interpretable Detection of Malaria Parasite in Red Blood Cells using Lower-dimensional Feature Space. IJCNN Anik Khan, Kishor Datta Gupta, Deepak Venugopal, Nirman Kumar
2020	J	`jnl`	CIDMP: Completely Interpretable Detection of Malaria Parasite in Red Blood Cells using Lower-dimensional Feature Space. CoRR Anik Khan, Kishor Datta Gupta, Deepak Venugopal, Nirman Kumar
2020	—	`conf`	Empirical Evaluation of the Ensemble Framework for Feature Selection in DDoS Attack. CSCloud/EdgeCom Saikat Das, Deepak Venugopal, Sajjan G. Shiva, Frederick T. Sheldon
2020	J	`jnl`	Ensemble Classifiers for Network Intrusion Detection Using a Novel Network Attack Dataset. Future Internet Ahmed M. Mahfouz, Abdullah Abuhussein, Deepak Venugopal, Sajjan G. Shiva
2020	—	`conf`	Taxonomy and Survey of Interpretable Machine Learning Method. SSCI Saikat Das, Namita Agarwal, Deepak Venugopal, Frederick T. Sheldon, Sajjan G. Shiva
2019	A	`conf`	Adaptive Rao-Blackwellisation in Gibbs Sampling for Probabilistic Graphical Models. AISTATS Craig Kelly, Somdeb Sarkhel, Deepak Venugopal
2019	—	`conf`	Comparative Analysis of ML Classifiers for Network Intrusion Detection. ICICT (2) Ahmed M. Mahfouz, Deepak Venugopal, Sajjan G. Shiva
2019	—	`conf`	DDoS Intrusion Detection Through Machine Learning Ensemble. QRS Companion Saikat Das, Ahmed M. Mahfouz, Deepak Venugopal, Sajjan G. Shiva
2019	J	`jnl`	Detecting Anomalous Online Reviewers: An Unsupervised Approach Using Mixture Models. J. Manag. Inf. Syst. Naveen Kumar, Deepak Venugopal, Liangfei Qiu, Subodha Kumar
2019	—	`conf`	Fine-Grained Explanations Using Markov Logic. ECML/PKDD (2) Khan Mohammad Al Farabi, Somdeb Sarkhel, Sanorita Dey, Deepak Venugopal
2019	A*	`conf`	On Lifted Inference Using Neural Embeddings. AAAI Mohammad Maminur Islam, Somdeb Sarkhel, Deepak Venugopal
2018	J	`jnl`	Detecting Review Manipulation on Online Platforms with Hierarchical Supervised Learning. J. Manag. Inf. Syst. Naveen Kumar, Deepak Venugopal, Liangfei Qiu, Subodha Kumar
2018	A	`conf`	Efficient Weight Learning in High-Dimensional Untied MLNs. AISTATS Khan Mohammad Al Farabi, Somdeb Sarkhel, Deepak Venugopal
2018	—	`conf`	Fine-Grained Crime Prediction in an Urban Neighborhood. ISC2 Christopher Kent, Deepak Venugopal
2018	A*	`conf`	Learning Mixtures of MLNs. AAAI Mohammad Maminur Islam, Somdeb Sarkhel, Deepak Venugopal
2018	—	`conf`	Scaling up Inference in MLNs with Spark. IEEE BigData Mohammad Maminur Islam, Khan Mohammad Al Farabi, Somdeb Sarkhel, Deepak Venugopal
2017	B	`conf`	Adaptive blocked Gibbs sampling for inference in probabilistic graphical models. IJCNN Mohammad Maminur Islam, Mohammad Khan Al Farabi, Deepak Venugopal
2017	J	`jnl`	Advances in Inference Methods for Markov Logic Networks. IEEE Intell. Informatics Bull. Deepak Venugopal
2017	A*	`conf`	Efficient Inference for Untied MLNs. IJCAI Somdeb Sarkhel, Deepak Venugopal, Nicholas Ruozzi, Vibhav Gogate
2016	B	`conf`	Joint Inference for Event Coreference Resolution. COLING Jing Lu, Deepak Venugopal, Vibhav Gogate, Vincent Ng
2016	B	`conf`	Joint Inference for Mode Identification in Tutorial Dialogues. COLING Deepak Venugopal, Vasile Rus
2016	A	`conf`	Non-parametric Domain Approximation for Scalable Gibbs Sampling in MLNs. UAI Deepak Venugopal, Somdeb Sarkhel, Kyle Cherry
2016	A*	`conf`	Scalable Training of Markov Logic Networks Using Approximate Counting. AAAI Somdeb Sarkhel, Deepak Venugopal, Tuan Anh Pham, Parag Singla, Vibhav Gogate
2015	A*	`conf`	Just Count the Satisfied Groundings: Scalable Local-Search and Sampling Based Inference in MLNs. AAAI Deepak Venugopal, Somdeb Sarkhel, Vibhav Gogate
2015	A*	`conf`	Scaling-Up Inference in Markov Logic. AAAI Deepak Venugopal
2014	—	`conf`	An Integer Polynomial Programming Based Framework for Lifted MAP Inference. NIPS Somdeb Sarkhel, Deepak Venugopal, Parag Singla, Vibhav Gogate
2014	—	`conf`	Evidence-Based Clustering for Scalable Inference in Markov Logic. StarAI@AAAI Deepak Venugopal, Vibhav Gogate
2014	—	`conf`	Evidence-Based Clustering for Scalable Inference in Markov Logic. ECML/PKDD (3) Deepak Venugopal, Vibhav Gogate
2014	A	`conf`	Lifted MAP Inference for Markov Logic Networks. AISTATS Somdeb Sarkhel, Deepak Venugopal, Parag Singla, Vibhav Gogate
2014	A*	`conf`	Relieving the Computational Bottleneck: Joint Inference for Event Extraction with High-Dimensional Features. EMNLP Deepak Venugopal, Chen Chen, Vibhav Gogate, Vincent Ng
2014	—	`conf`	Scaling-up Importance Sampling for Markov Logic Networks. NIPS Deepak Venugopal, Vibhav Gogate
2013	A	`conf`	Dynamic Blocking and Collapsing for Gibbs Sampling. UAI Deepak Venugopal, Vibhav Gogate
2013	J	`jnl`	Dynamic Blocking and Collapsing for Gibbs Sampling. CoRR Deepak Venugopal, Vibhav Gogate
2013	A*	`conf`	GiSS: Combining Gibbs Sampling and SampleSearch for Inference in Mixed Probabilistic and Deterministic Graphical Models. AAAI Deepak Venugopal, Vibhav Gogate
2012	A*	`conf`	Advances in Lifted Importance Sampling. AAAI Vibhav Gogate, Abhay Kumar Jha, Deepak Venugopal
2012	—	`conf`	On Lifting the Gibbs Sampling Algorithm. NIPS Deepak Venugopal, Vibhav Gogate
2012	—	`conf`	On Lifting the Gibbs Sampling Algorithm. StarAI@UAI Deepak Venugopal, Vibhav Gogate
2008	J	`jnl`	Efficient signature based malware detection on mobile devices. Mob. Inf. Syst. Deepak Venugopal, Guoning Hu
2007	C	`conf`	A Malware Signature Extraction and Detection Method Applied to Mobile Networks. IPCCC Guoning Hu, Deepak Venugopal
2006	—	`conf`	An efficient signature representation and matching method for mobile devices. WICON Deepak Venugopal
2006	C	`conf`	Intelligent virus detection on mobile devices. PST Deepak Venugopal, Guoning Hu, Nicoleta Roman