Sayantan Kumar

19 papers A* 2Journal 13Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AgileFormer: Spatially agile and scalable transformer for medical image segmentation. Biomed. Signal Process. Control. Peijie Qiu, Jin Yang, Sayantan Kumar, Soumyendu Sekhar Ghosh, Aristeidis Sotiras
2026	A*	`conf`	Forecasting Clinical Risk from Textual Time Series: Structuring Narratives for Temporal AI in Healthcare. AAAI Shahriar Noroozizadeh, Sayantan Kumar, Jeremy C. Weiss
2026	J	`jnl`	Multimodal normative modeling in Alzheimers Disease with introspective variational autoencoders. CoRR Sayantan Kumar, Peijie Qiu, Aristeidis Sotiras
2025	J	`jnl`	Forecasting from Clinical Textual Time Series: Adaptations of the Encoder and Decoder Language Model Families. CoRR Shahriar Noroozizadeh, Sayantan Kumar, Jeremy C. Weiss
2025	A*	`conf`	Multimodal Variational Autoencoder: A Barycentric View. AAAI Peijie Qiu, Wenhui Zhu, Sayantan Kumar, Xiwen Chen, Jin Yang, Xiaotong Sun, Abolfazl Razi, Yalin Wang, Aristeidis Sotiras
2025	J	`jnl`	PMOA-TTS: Introducing the PubMed Open Access Textual Times Series Corpus. CoRR Shahriar Noroozizadeh, Sayantan Kumar, George H. Chen, Jeremy C. Weiss
2024	J	`jnl`	AgileFormer: Spatially Agile Transformer UNet for Medical Image Segmentation. CoRR Peijie Qiu, Jin Yang, Sayantan Kumar, Soumyendu Sekhar Ghosh, Aristeidis Sotiras
2024	J	`jnl`	Analysing heterogeneity in Alzheimer Disease using multimodal normative modelling on ATN biomarkers. CoRR Sayantan Kumar, Thomas Earnest, Braden Yang, Deydeep Kothapalli, Tammie L. S. Benzinger, Brian A. Gordon, Philip R. O. Payne, Aristeidis Sotiras
2024	J	`jnl`	HiMAL: A Multimodal Hierarchical Multi-task Auxiliary Learning framework for predicting and explaining Alzheimer disease progression. CoRR Sayantan Kumar, Sean C. Yu, Andrew P. Michelson, Thomas George Kannampallil, Philip R. O. Payne
2024	—	`conf`	Improving Normative Modeling for Multi-Modal Neuroimaging Data Using Mixture-of-Product-of-Experts Variational Autoencoders. ISBI Sayantan Kumar, Philip R. O. Payne, Aristeidis Sotiras
2024	J	`jnl`	Multimodal Variational Autoencoder: a Barycentric View. CoRR Peijie Qiu, Wenhui Zhu, Sayantan Kumar, Xiwen Chen, Xiaotong Sun, Jin Yang, Abolfazl Razi, Yalin Wang, Aristeidis Sotiras
2023	J	`jnl`	Improving Normative Modeling for Multi-modal Neuroimaging Data using mixture-of-product-of-experts variational autoencoders. CoRR Sayantan Kumar, Philip R. O. Payne, Aristeidis Sotiras
2023	—	`conf`	Normative modeling using multimodal variational autoencoders to identify abnormal brain volume deviations in Alzheimer's disease. Computer-Aided Diagnosis Sayantan Kumar, Philip R. O. Payne, Aristeidis Sotiras
2022	J	`jnl`	Identifying Interpretable Clinical Subtypes withinHeterogeneous Dementia Clinic Population. CoRR Sayantan Kumar
2022	—	`conf`	Machine Learning for Health (ML4H) 2022. ML4H@NeurIPS Antonio Parziale, Monica Agrawal, Shengpu Tang, Kristen Severson, Luis Oala, Adarsh Subbaswamy, Sayantan Kumar, Elora D. M. Schörverth, Stefan Hegselmann, Helen Zhou, Ghada Zamzmi, Purity Mugambi, Elena Sizikova, Girmaw Abebe Tadesse, Yuyin Zhou, Taylor W. Killian, Haoran Zhang, Fahad Kamran, Andrea Hobby, Mars Huang, Ahmed M. Alaa, Harvineet Singh, Irene Y. Chen, Shalmali Joshi
2022	—	`conf`	Self-explaining neural network with concept-based explanations for ICU mortality prediction. BCB Sayantan Kumar, Sean C. Yu, Thomas George Kannampallil, Zachary B. Abrams, Andrew P. Michelson, Philip R. O. Payne
2021	J	`jnl`	Machine learning for modeling the progression of Alzheimer disease dementia using clinical data: a systematic literature review. CoRR Sayantan Kumar, Inez Y. Oh, Suzanne E. Schindler, Albert M. Lai, Philip R. O. Payne, Aditi Gupta
2021	J	`jnl`	NormVAE: Normative Modeling on Neuroimaging Data using Variational Autoencoders. CoRR Sayantan Kumar, Aristeidis Sotiras
2021	J	`jnl`	Self-explaining Neural Network with Plausible Explanations. CoRR Sayantan Kumar, Sean C. Yu, Andrew P. Michelson, Philip R. O. Payne