| 2025 | ECAI | Improving Text Style Transfer Using Masked Diffusion Language Models with Inference-Time Scaling. | Tejomay Kishor Padole, Suyash P. Awate, Pushpak Bhattacharyya |
| 2025 | WACV | Reviving Poor Object Segmentations in OOD Medical Images using Variational-Deep-PCA Modeling on Segmentation Maps with Sampling-Free Learning. | Jimut B. Pal, Shantanu Welling, Himali Saini, Suyash P. Awate |
| 2024 | ICIP | A Hard Convex-Shape Constraint In Dnns For Object Segmentation. | Jimut B. Pal, Suyash P. Awate |
| 2024 | ICIP | Adversarial EM For Partially-Supervised Image-Quality Enhancement: Application To Low-Dose Pet Imaging. | Vatsala Sharma, Suyash P. Awate |
| 2024 | MICCAI | Convex Segments for Convex Objects Using DNN Boundary Tracing and Graduated Optimization. | Jimut B. Pal, Suyash P. Awate |
| 2023 | DICTA | Deep Semi-supervised Anomaly Detection Using VQ-VAE. | Renuka Sharma, Hengcan Shi, Jianfei Cai, Suyash P. Awate, Nick Birbilis |
| 2023 | ICIP | Deep Variational Segmentation of Topology-Constrained Object Sets, with Correlated Uncertainty Models, for Robustness to Degradations. | Akshay V. Gaikwad, Harshit Varma, Suyash P. Awate |
| 2022 | WACV | A Semi-supervised Generalized VAE Framework for Abnormality Detection using One-Class Classification. | Renuka Sharma, Satvik Mashkaria, Suyash P. Awate |
| 2020 | ICPR | Generative Deep-Neural-Network Mixture Modeling with Semi-Supervised MinMax+EM Learning. | Nilay Pande, Suyash P. Awate |
| 2020 | ICPR | A Bayesian Deep CNN Framework for Reconstructing k-t-Undersampled Resting-fMRI. | Karan Taneja, Prachi H. Kulkarni, S. N. Merchant, Suyash P. Awate |
| 2020 | ICPR | Learning Image Inpainting from Incomplete Images using Self-Supervision. | Sriram Yenamandra, Ansh Khurana, Rohit Jena, Suyash P. Awate |
| 2019 | ICIP | Bayesian Reconstruction of Undersampled Multicoil Hardi. | Kratika Gupta, Suyash P. Awate |
| 2019 | ICIP | Random Forests for Simultaneous-Multislice (SMS) Undersampled HARDI Reconstruction and Uncertainty Estimation. | Kratika Gupta, Suyash P. Awate |
| 2019 | ICIP | Semi-Supervised Robust One-Class Classification in RKHS for Abnormality Detection in Medical Images. | Nitin Kumar, Sharat Chandran, Ajit V. Rajwade, Suyash P. Awate |
| 2019 | MICCAI | Joint Reconstruction of PET + Parallel-MRI in a Bayesian Coupled-Dictionary MRF Framework. | Viswanath P. Sudarshan, Kratika Gupta, Gary F. Egan, Zhaolin Chen, Suyash P. Awate |
| 2019 | MICCAI | A Mixed-Supervision Multilevel GAN Framework for Image Quality Enhancement. | Uddeshya Upadhyay, Suyash P. Awate |
| 2018 | ICMLA | Sparse Kernel PCA for Outlier Detection. | Rudrajit Das, Aditya Golatkar, Suyash P. Awate |
| 2018 | MICCAI | Perfect MCMC Sampling in Bayesian MRFs for Uncertainty Estimation in Segmentation. | Saurabh Garg, Suyash P. Awate |
| 2018 | MICCAI | MS-Net: Mixed-Supervision Fully-Convolutional Networks for Full-Resolution Segmentation. | Meet P. Shah, S. N. Merchant, Suyash P. Awate |
| 2018 | MICCAI | Joint PET+MRI Patch-Based Dictionary for Bayesian Random Field PET Reconstruction. | Viswanath P. Sudarshan, Zhaolin Chen, Suyash P. Awate |
| 2017 | ICIP | Kernel generalized Gaussian and robust statistical learning for abnormality detection in medical images. | Nitin Kumar, Ajit V. Rajwade, Sharat Chandran, Suyash P. Awate |
| 2017 | ICIP | Leaf classification using marginalized shape context and shape+texture dual-path deep convolutional neural network. | Meet P. Shah, Sougata Singha, Suyash P. Awate |
| 2017 | MICCAI | Kernel Generalized-Gaussian Mixture Model for Robust Abnormality Detection. | Nitin Kumar, Ajit V. Rajwade, Sharat Chandran, Suyash P. Awate |
| 2016 | ICPR | Robust kernel principal nested spheres. | Suyash P. Awate, Manik Dhar, Nilesh Kulkarni |
| 2016 | MICCAI | Riemannian Statistical Analysis of Cortical Geometry with Robustness to Partial Homology and Misalignment. | Suyash P. Awate, Richard M. Leahy, Anand A. Joshi |
| 2016 | MICCAI | Hierarchical Generative Modeling and Monte-Carlo EM in Riemannian Shape Space for Hypothesis Testing. | Saurabh J. Shigwan, Suyash P. Awate |
| 2015 | MICCAI | A Statistical Model for Smooth Shapes in Kendall Shape Space. | Akshay V. Gaikwad, Saurabh J. Shigwan, Suyash P. Awate |
| 2014 | MICCAI | Hierarchical Bayesian Modeling, Estimation, and Sampling for Multigroup Shape Analysis. | Yen-Yun Yu, P. Thomas Fletcher, Suyash P. Awate |
| 2013 | ICML | Adaptive Sparsity in Gaussian Graphical Models. | Eleanor Wong, Suyash P. Awate, P. Thomas Fletcher |
| 2013 | MICCAI | Modeling 4D Changes in Pathological Anatomy Using Domain Adaptation: Analysis of TBI Imaging Using a Tumor Database. | Bo Wang, Marcel Prastawa, Avishek Saha, Suyash P. Awate, Andrei Irimia, Micah C. Chambers, Paul M. Vespa, John D. Van Horn, Valerio Pascucci, Guido Gerig |
| 2012 | MICCAI | How Many Templates Does It Take for a Good Segmentation?: Error Analysis in Multiatlas Segmentation as a Function of Database Size. | Suyash P. Awate, Peihong Zhu, Ross T. Whitaker |
| 2012 | MICCAI | Group Analysis of Resting-State fMRI by Hierarchical Markov Random Fields. | Wei Liu, Suyash P. Awate, P. Thomas Fletcher |
| 2011 | MICCAI | Monte Carlo Expectation Maximization with Hidden Markov Models to Detect Functional Networks in Resting-State fMRI. | Wei Liu, Suyash P. Awate, Jeffrey S. Anderson, Deborah A. Yurgelun-Todd, P. Thomas Fletcher |
| 2011 | MICCAI | Fast Shape-Based Nearest-Neighbor Search for Brain MRIs Using Hierarchical Feature Matching. | Peihong Zhu, Suyash P. Awate, Samuel Gerber, Ross T. Whitaker |
| 2009 | MICCAI | Gender Differences in Cerebral Cortical Folding: Multivariate Complexity-Shape Analysis with Insights into Handling Brain-Volume Differences. | Suyash P. Awate, Paul A. Yushkevich, Daniel J. Licht, James C. Gee |
| 2009 | MICCAI | A Tract-Specific Framework for White Matter Morphometry Combining Macroscopic and Microscopic Tract Features. | Hui Zhang, Suyash P. Awate, Sandhitsu R. Das, John H. Woo, Elias R. Melhem, James C. Gee, Paul A. Yushkevich |
| 2009 | MICCAI | Automatic Correction of Intensity Nonuniformity from Sparseness of Gradient Distribution in Medical Images. | Yuanjie Zheng, Murray Grossman, Suyash P. Awate, James C. Gee |
| 2008 | MICCAI | 3D Cerebral Cortical Morphometry in Autism: Increased Folding in Children and Adolescents in Frontal, Parietal, and Temporal Lobes. | Suyash P. Awate, Lawrence Win, Paul A. Yushkevich, Robert T. Schultz, James C. Gee |
| 2007 | MICCAI | Fuzzy Nonparametric DTI Segmentation for Robust Cingulum-Tract Extraction. | Suyash P. Awate, Hui Zhang, James C. Gee |
| 2007 | MICCAI | Clinical Neonatal Brain MRI Segmentation Using Adaptive Nonparametric Data Models and Intensity-Based Markov Priors. | Zhuang Song, Suyash P. Awate, Daniel J. Licht, James C. Gee |
| 2006 | ECCV | Unsupervised Texture Segmentation with Nonparametric Neighborhood Statistics. | Suyash P. Awate, Tolga Tasdizen, Ross T. Whitaker |
| 2005 | CVPR | Higher-Order Image Statistics for Unsupervised, Information-Theoretic, Adaptive, Image Filtering. | Suyash P. Awate, Ross T. Whitaker |
| 2005 | MICCAI | MRI Tissue Classification with Neighborhood Statistics: A Nonparametric, Entropy-Minimizing Approach. | Tolga Tasdizen, Suyash P. Awate, Ross T. Whitaker, Norman L. Foster |