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

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

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

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

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

Study of Different Deep Learning Approach with Explainable AI for Screening Patients with COVID-19 Symptoms: Using CT Scan and Chest X-ray Image Dataset. - Md. Manjurul Ahsan; Kishor Datta Gupta; Mohammad Maminur Islam; Sajib Sen; Md. Lutfar Rahman; Mohammad Shakhawat Hossain (CoRR, 2020)

COVID-19 Symptoms Detection Based on NasNetMobile with Explainable AI Using Various Imaging Modalities. - Md. Manjurul Ahsan; Kishor Datta Gupta; Mohammad Maminur Islam; Sajib Sen; Md. Lutfar Rahman; Mohammad Shakhawat Hossain (Mach. Learn. Knowl. Extr., 2020)

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

MemFlex: A Hybrid Memory System to Boost Cost of Ownership in Data Centers. - Chandranil Chakraborttii; Mohammad Maminur Islam (COMPSAC, 2024)

TAP: Transformers Driven Adaptive Prefetching for Hybrid Memory Systems. - Chandranil Chakraborttii; Mohammad Maminur Islam (ISCMI, 2024)

Enhancing Graph Representation Learning with WalkLM for Effective Community Detection. - Hyun Lee; Mohammad Maminur Islam; Chris Yi; Chandranil Nil Chakraborttii (NSysS, 2024)

Scalability Matters: Overcoming Challenges in InstructGLM with Similarity-Degree-Based Sampling. - Hyun Lee; Chris Yi; Mohammad Maminur Islam; B. D. S. Aritra (CoRR, 2025)