Discriminative boosted Bayes networks for learning multiple cardiovascular procedures. - Nandini Ramanan; Shuo Yang 004; Shaun J. Grannis; Sriraam Natarajan (BIBM, 2017)

Boosting for Postpartum Depression Prediction. - Sriraam Natarajan; Annu Prabhakar; Nandini Ramanan; Anna N. Baglione; Katie A. Siek; Kay Connelly (CHASE, 2017)

On Whom Should I Perform this Lab Test Next? An Active Feature Elicitation Approach. - Sriraam Natarajan; Srijita Das 001; Nandini Ramanan; Gautam Kunapuli; Predrag Radivojac (IJCAI, 2018)

One-Shot Induction of Generalized Logical Concepts via Human Guidance. - Mayukh Das; Nandini Ramanan; Janardhan Rao Doppa; Sriraam Natarajan (CoRR, 2019)

Discriminative Non-Parametric Learning of Arithmetic Circuits. - Nandini Ramanan; Mayukh Das; Kristian Kersting; Sriraam Natarajan (PGM, 2020)

Causal Learning From Predictive Modeling for Observational Data. - Nandini Ramanan; Sriraam Natarajan (Frontiers Big Data, 2020)

Few-Shot Induction of Generalized Logical Concepts via Human Guidance. - Mayukh Das; Nandini Ramanan; Janardhan Rao Doppa; Sriraam Natarajan (Frontiers Robotics AI, 2020)

Interactive Transfer Learning in Relational Domains. - Raksha Kumaraswamy; Nandini Ramanan; Phillip Odom; Sriraam Natarajan (Künstliche Intell., 2020)

Boosted Embeddings for Time-Series Forecasting. - Sankeerth Rao Karingula; Nandini Ramanan; Rasool Tahmasbi; Mehrnaz Amjadi; Deokwoo Jung; Ricky Si; Charanraj Thimmisetty; Luisa F. Polanía; Marjorie Sayer; Jake Taylor; Claudionor Nunes Coelho (LOD, 2021)

Boosted Embeddings for Time Series Forecasting. - Sankeerth Rao Karingula; Nandini Ramanan; Rasool Tahsambi; Mehrnaz Amjadi; Deokwoo Jung; Ricky Si; Charanraj Thimmisetty; Claudionor José Nunes Coelho Jr. (CoRR, 2021)

Log2NS: Enhancing Deep Learning Based Analysis of Logs With Formal to Prevent Survivorship Bias. - Charanraj Thimmisetty; Praveen Tiwari; Didac Gil de la Iglesia; Nandini Ramanan; Marjorie Sayer; Viswesh Ananthakrishnan; Claudionor José Nunes Coelho Jr. (CoRR, 2021)

Time Series Anomaly Detection with label-free Model Selection. - Deokwoo Jung; Nandini Ramanan; Mehrnaz Amjadi; Sankeerth Rao Karingula; Jake Taylor; Claudionor José Nunes Coelho Jr. (CoRR, 2021)

Real-time Drift Detection on Time-series Data. - Nandini Ramanan; Rasool Tahmasbi; Marjorie Sayer; Deokwoo Jung; Shalini Hemachandran; Claudionor José Nunes Coelho Jr. (CoRR, 2021)

Structure learning for relational logistic regression: an ensemble approach. - Nandini Ramanan; Gautam Kunapuli; Tushar Khot; Bahare Fatemi; Seyed Mehran Kazemi; David Poole 001; Kristian Kersting; Sriraam Natarajan (Data Min. Knowl. Discov., 2021)

Relational Active Feature Elicitation for DDDAS. - Nandini Ramanan; Phillip Odom; Erik Blasch; Kristian Kersting; Sriraam Natarajan (DDDAS, 2022)

Contrastive Credibility Propagation for Reliable Semi-Supervised Learning. - Brody Kutt; Pamela Toman; Xavier Mignot; Sujit Rokka Chhetri; Shan Huang; Nandini Ramanan; Min Du; William Hewlett (CoRR, 2022)

Active Feature Acquisition via Human Interaction in Relational domains. - Nandini Ramanan; Phillip Odom; Kristian Kersting; Sriraam Natarajan (COMAD/CODS, 2023)

Active feature elicitation: An unified framework. - Srijita Das 001; Nandini Ramanan; Gautam Kunapuli; Predrag Radivojac; Sriraam Natarajan (Frontiers Artif. Intell., 2023)

Contrastive Credibility Propagation for Reliable Semi-supervised Learning. - Brody Kutt; Pralay Ramteke; Xavier Mignot; Pamela Toman; Nandini Ramanan; Sujit Rokka Chhetri; Shan Huang; Min Du; William Hewlett (AAAI, 2024)