Deep learning based large scale handwritten Devanagari character recognition. - Shailesh Acharya; Ashok Kumar Pant; Prashnna Kumar Gyawali (SKIMA, 2015)

Devanagari Handwritten Character Dataset. - Shailesh Acharya; Prashnna K. Gyawali (UCI-MLR, 2016)

Atrial Fibrillation Classification from a Short Single Lead ECG Recording Using Hierarchical Classifier. - Erin Coppola; Prashnna K. Gyawali; Nihar Vanjara; Daniel Giaime; Linwei Wang (CinC, 2017)

Automatic Coordinate Prediction of the Exit of Ventricular Tachycardia from 12-Lead Electrocardiogram. - Prashnna K. Gyawali; Shuhang Chen; Huafeng Liu 003; B. Milan Horácek; John L. Sapp; Linwei Wang (CinC, 2017)

Disentangling inter-subject variations: Automatic localization of ventricular tachycardia origin from 12-lead electrocardiograms. - Shuhang Chen; Prashnna K. Gyawali; Huafeng Liu 003; B. Milan Horácek; John L. Sapp; Linwei Wang (ISBI, 2017)

Learning Disentangled Representation from 12-Lead Electrograms: Application in Localizing the Origin of Ventricular Tachycardia. - Prashnna K. Gyawali; B. Milan Horácek; John L. Sapp; Linwei Wang (AAAI Workshops, 2018)

Generative Modeling and Inverse Imaging of Cardiac Transmembrane Potential. - Sandesh Ghimire; Jwala Dhamala; Prashnna Kumar Gyawali; John L. Sapp; Milan Horacek; Linwei Wang (MICCAI (2), 2018)

Improving Generalization of Sequence Encoder-Decoder Networks for Inverse Imaging of Cardiac Transmembrane Potential. - Sandesh Ghimire; Prashnna Kumar Gyawali; John L. Sapp; Milan Horacek; Linwei Wang (CoRR, 2018)

Deep Generative Model with Beta Bernoulli Process for Modeling and Learning Confounding Factors. - Prashnna K. Gyawali; Cameron Knight; Sandesh Ghimire; B. Milan Horácek; John L. Sapp; Linwei Wang (CoRR, 2018)

Improving Disentangled Representation Learning with the Beta Bernoulli Process. - Prashnna K. Gyawali; Zhiyuan Li 007; Cameron Knight; Sandesh Ghimire; B. Milan Horácek; John L. Sapp; Linwei Wang (ICDM, 2019)

Improving Generalization of Deep Networks for Inverse Reconstruction of Image Sequences. - Sandesh Ghimire; Prashnna Kumar Gyawali; Jwala Dhamala; John L. Sapp; Milan Horacek; Linwei Wang (IPMI, 2019)

Semi-supervised Learning by Disentangling and Self-ensembling over Stochastic Latent Space. - Prashnna Kumar Gyawali; Zhiyuan Li 007; Sandesh Ghimire; Linwei Wang (MICCAI (6), 2019)

Wavelets to the Rescue: Improving Sample Quality of Latent Variable Deep Generative Models. - Prashnna K. Gyawali; Rudra Saha; Linwei Wang; V. S. R. Veeravasarapu; Maneesh Singh 001 (CoRR, 2019)

Enhancing Mixup-based Semi-Supervised Learning with Explicit Lipschitz Regularization. - Prashnna Kumar Gyawali; Sandesh Ghimire; Linwei Wang (ICDM, 2020)

Progressive Learning and Disentanglement of Hierarchical Representations. - Zhiyuan Li 007; Jaideep Vitthal Murkute; Prashnna Kumar Gyawali; Linwei Wang (ICLR, 2020)

Semi-supervised Medical Image Classification with Global Latent Mixing. - Prashnna Kumar Gyawali; Sandesh Ghimire; Pradeep Bajracharya; Zhiyuan Li 007; Linwei Wang (MICCAI (1), 2020)

Learning Geometry-Dependent and Physics-Based Inverse Image Reconstruction. - Xiajun Jiang; Sandesh Ghimire; Jwala Dhamala; Zhiyuan Li 007; Prashnna Kumar Gyawali; Linwei Wang (MICCAI (6), 2020)

A hybrid machine learning approach to localizing the origin of ventricular tachycardia using 12-lead electrocardiograms. - Ryan Missel; Prashnna K. Gyawali; Jaideep Vitthal Murkute; Zhiyuan Li 007; Shijie Zhou; Amir AbdelWahab; Jason Davis; James Warren; John L. Sapp; Linwei Wang (Comput. Biol. Medicine, 2020)

Reliable Estimation of Kullback-Leibler Divergence by Controlling Discriminator Complexity in the Reproducing Kernel Hilbert Space. - Sandesh Ghimire; Prashnna K. Gyawali; Linwei Wang (CoRR, 2020)

Sequential Factorized Autoencoder for Localizing the Origin of Ventricular Activation From 12-Lead Electrocardiograms. - Prashnna Kumar Gyawali; B. Milan Horácek; John L. Sapp; Linwei Wang (IEEE Trans. Biomed. Eng., 2020)

Latent-optimization based Disease-aware Image Editing for Medical Image Augmentation. - Aakash Saboo; Prashnna K. Gyawali; Ankit Shukla 001; Manoj Sharma; Neeraj Jain; Linwei Wang (BMVC, 2021)

Semi-Supervised Learning for Eye Image Segmentation. - Aayush Kumar Chaudhary; Prashnna K. Gyawali; Linwei Wang; Jeff B. Pelz (ETRA Short Papers, 2021)

Deep Adaptive Electrocardiographic Imaging with Generative Forward Model for Error Reduction. - Maryam Toloubidokhti; Prashnna K. Gyawali; Omar A. Gharbia; Xiajun Jiang; Jaume Coll-Font; Jake A. Bergquist; Brian Zenger; Wilson W. Good; Dana H. Brooks; Rob S. MacLeod; Linwei Wang (FIMH, 2021)

Interpretable Modeling and Reduction of Unknown Errors in Mechanistic Operators. - Maryam Toloubidokhti; Nilesh Kumar; Zhiyuan Li 007; Prashnna K. Gyawali; Brian Zenger; Wilson W. Good; Rob S. MacLeod; Linwei Wang (MICCAI (8), 2022)

Ensembling improves stability and power of feature selection for deep learning models. - Prashnna K. Gyawali; Xiaoxia Liu; James Zou 001; Zihuai He (MLCB, 2022)

Improving genetic risk prediction across diverse population by disentangling ancestry representations. - Prashnna K. Gyawali; Yann Le Guen; Xiaoxia Liu; Hua Tang; James Zou 001; Zihuai He (CoRR, 2022)

Learning to Disentangle Inter-Subject Anatomical Variations in Electrocardiographic Data. - Prashnna K. Gyawali; Jaideep Vitthal Murkute; Maryam Toloubidokhti; Xiajun Jiang; B. Milan Horácek; John L. Sapp; Linwei Wang (IEEE Trans. Biomed. Eng., 2022)

Continual Unsupervised Disentangling of Self-Organizing Representations. - Zhiyuan Li 007; Xiajun Jiang; Ryan Missel; Prashnna Kumar Gyawali; Nilesh Kumar; Linwei Wang (ICLR, 2023)

Learning Transferable Object-Centric Diffeomorphic Transformations for Data Augmentation in Medical Image Segmentation. - Nilesh Kumar; Prashnna K. Gyawali; Sandesh Ghimire; Linwei Wang (MICCAI (2), 2023)

T2FNorm: Extremely Simple Scaled Train-time Feature Normalization for OOD Detection. - Sudarshan Regmi; Bibek Panthi; Sakar Dotel; Prashnna K. Gyawali; Danail Stoyanov; Binod Bhattarai (CoRR, 2023)

Multimodal Federated Learning in Healthcare: a review. - Jacob Thrasher; Alina Devkota; Prasiddha Siwakoti; Rohit Chivukula; Pranav Poudel; Chaunbo Hu; Binod Bhattarai; Prashnna K. Gyawali (CoRR, 2023)

Can AI Keep You Safe? A Study of Large Language Models for Phishing Detection. - Robin Chataut; Prashnna Kumar Gyawali; Yusuf Usman (CCWC, 2024)

Spam No More: A Cross-Model Analysis of Machine Learning Techniques and Large Language Model Efficacies. - Robin Chataut; Aadesh Upadhyay; Yusuf Usman; Mary Nankya; Prashnna K. Gyawali (CSNet, 2024)

T2FNorm: Train-time Feature Normalization for OOD Detection in Image Classification. - Sudarshan Regmi; Bibek Panthi; Sakar Dotel; Prashnna K. Gyawali; Danail Stoyanov; Binod Bhattarai (CVPR Workshops, 2024)

ReweightOOD: Loss Reweighting for Distance-based OOD Detection. - Sudarshan Regmi; Bibek Panthi; Yifei Ming; Prashnna K. Gyawali; Danail Stoyanov; Binod Bhattarai (CVPR Workshops, 2024)

Multi-Task Learning for Material Property Prediction. - Chowdhury Mohammad Abid Rahman; Nishat B. Alam; Amr S. El-Wakeel; JuHyeong Ryu; Prashnna K. Gyawali (ICMLA, 2024)

Segmentation of Maya Hieroglyphs through Fine-Tuned Foundation Models. - FNU Shivam; Megan Leight; Mary Kate Kelly; Claire Davis 003; Kelsey Clodfelter; Jacob Thrasher; Chowdhury Mohammad Abid Rahman; Yenumula Reddy; Prashnna K. Gyawali (ICMLA, 2024)

TTA-OOD: Test-Time Augmentation for Improving Out-of-Distribution Detection in Gastrointestinal Vision. - Sandesh Pokhrel; Sanjay Bhandari; Eduard Vazquez; Tryphon Lambrou; Prashnna K. Gyawali; Binod Bhattarai (DEMI@MICCAI, 2024)

CAR-MFL: Cross-Modal Augmentation by Retrieval for Multimodal Federated Learning with Missing Modalities. - Pranav Poudel; Prashant Shrestha; Sanskar Amgain; Yash Raj Shrestha; Prashnna K. Gyawali; Binod Bhattarai (MICCAI (10), 2024)

Enhancing Retinal Disease Classification from OCTA Images via Active Learning Techniques. - Jacob Thrasher; Annahita Amireskandari; Prashnna K. Gyawali (DEMI@MICCAI, 2024)

TE-SSL: Time and Event-Aware Self Supervised Learning for Alzheimer's Disease Progression Analysis. - Jacob Thrasher; Alina Devkota; Ahmad P. Tafti; Binod Bhattarai; Prashnna K. Gyawali (MICCAI (12), 2024)

Enhancing Phishing Detection with AI: A Novel Dataset and Comprehensive Analysis Using Machine Learning and Large Language Models. - Robin Chataut; Yusuf Usman; Chowdhury Mohammad Abid Rahman; Sohan Gyawali; Prashnna K. Gyawali (UEMCON, 2024)

The Dark Side of AI: Large Language Models as Tools for Cyber Attacks on Vehicle Systems. - Yusuf Usman; Prashnna K. Gyawali; Sohan Gyawali; Robin Chataut (UEMCON, 2024)

Segmentation of Maya hieroglyphs through fine-tuned foundation models. - FNU Shivam; Megan Leight; Mary Kate Kelly; Claire Davis 003; Kelsey Clodfelter; Jacob Thrasher; Yenumula Reddy; Prashnna K. Gyawali (CoRR, 2024)

TE-SSL: Time and Event-aware Self Supervised Learning for Alzheimer's Disease Progression Analysis. - Jacob Thrasher; Alina Devkota; Ahmed Tafti; Binod Bhattarai; Prashnna K. Gyawali (CoRR, 2024)

Enhancing material property prediction with ensemble deep graph convolutional networks. - Chowdhury Mohammad Abid Rahman; Ghadendra Bhandari; Nasser M. Nasrabadi; Aldo H. Romero; Prashnna K. Gyawali (CoRR, 2024)

Is Generative AI the Next Tactical Cyber Weapon For Threat Actors? Unforeseen Implications of AI Generated Cyber Attacks. - Yusuf Usman; Aadesh Upadhyay; Prashnna K. Gyawali; Robin Chataut (CoRR, 2024)

NCDD: Nearest Centroid Distance Deficit for Out-Of-Distribution Detection in Gastrointestinal Vision. - Sandesh Pokhrel; Sanjay Bhandari; Sharib Ali; Tryphon Lambrou; Anh Nguyen 003; Yash Raj Shrestha; Angus Watson; Danail Stoyanov; Prashnna K. Gyawali; Binod Bhattarai (CoRR, 2024)

Explainable AI for Interpretable and Model-Agnostic Energy Consumption Prediction. - Cosmas Ifeanyi Nwakanma; Love Allen Chijioke Ahakonye; Judith Nkechinyere Njoku; Prashnna K. Gyawali; Anurag K. Srivastava 001 (IAS, 2025)

CURE: Centroid-guided Unsupervised Representation Erasure for Facial Recognition Systems. - FNU Shivam; Nima Najafzadeh; Yenumula Reddy; Prashnna K. Gyawali (IJCB, 2025)

Effect of Data Augmentation on Conformal Prediction for Diabetic Retinopathy. - Rizwan Ahamed; Annahita Amireskandari; Joel Palko; Carol Laxson; Binod Bhattarai; Prashnna K. Gyawali (DEMI@MICCAI, 2025)

Addressing Bias in VLMs for Glaucoma Detection Without Protected Attribute Supervision. - Ahsan Habib Akash; Greg Murray; Annahita Amireskandari; Joel Palko; Carol Laxson; Binod Bhattarai; Prashnna K. Gyawali (DEMI@MICCAI, 2025)

NERO: Explainable Out-of-Distribution Detection with Neuron-Level Relevance in Gastrointestinal Imaging. - Anju Chhetri; Jari Korhonen; Prashnna K. Gyawali; Binod Bhattarai (MICCAI (10), 2025)

Out-of-Distribution Detection in Gastrointestinal Vision by Estimating Nearest Centroid Distance Deficit. - Sandesh Pokhrel; Sanjay Bhandari; Sharib Ali; Tryphon Lambrou; Anh Nguyen 003; Yash Raj Shrestha; Angus Watson; Danail Stoyanov; Prashnna K. Gyawali; Binod Bhattarai (MIUA (2), 2025)

Multimodal Federated Learning with Missing Modalities Through Feature Imputation Network. - Pranav Poudel; Aavash Chhetri; Prashnna K. Gyawali; Georgios Leontidis; Binod Bhattarai (MIUA (1), 2025)

AutoTA: A Dynamic Intent-Based Virtual Teaching Assistant for Students Using Open Source LLMs. - Rajashree Dahal; Greg Murray; Robin Chataut; Mohamed Hefeida; Anurag Srivastava 001; Prashnna K. Gyawali (IEEE Access, 2025)

Supervised Pretraining for Material Property Prediction. - Chowdhury Mohammad Abid Rahman; Aldo H. Romero; Prashnna K. Gyawali (CoRR, 2025)

Federated Foundation Model for GI Endoscopy Images. - Alina Devkota; Annahita Amireskandari; Joel Palko; Shyam Thakkar; Donald Adjeroh; Xiajun Jiang; Binod Bhattarai; Prashnna K. Gyawali (CoRR, 2025)

NERO: Explainable Out-of-Distribution Detection with Neuron-level Relevance. - Anju Chhetri; Jari Korhonen; Prashnna K. Gyawali; Binod Bhattarai (CoRR, 2025)

Local K-Similarity Constraint for Federated Learning with Label Noise. - Sanskar Amgain; Prashant Shrestha; Bidur Khanal; Alina Devkota; Yash Raj Shrestha; Seungryul Baek; Prashnna K. Gyawali; Binod Bhattarai (CoRR, 2025)

Local $K$-Similarity Constraint for Medical Federated Learning with Label Noise. - Sanskar Amgain; Prashant Shrestha; Bidur Khanal; Alina Devkota; Yash Raj Shrestha; Sengryul Baek; Prashnna K. Gyawali; Binod Bhattarai (ISBI, 2026)

Med-MMFL: A Multimodal Federated Learning Benchmark in Healthcare. - Aavash Chhetri; Bibek Niroula; Pratik Shrestha; Yash Raj Shrestha; Lesley A. Anderson; Prashnna K. Gyawali; Loris Bazzani; Binod Bhattarai (CoRR, 2026)

FedVG: Gradient-Guided Aggregation for Enhanced Federated Learning. - Alina Devkota; Jacob Thrasher; Donald Adjeroh; Binod Bhattarai; Prashnna K. Gyawali (CoRR, 2026)

Investigating Trustworthiness of Nonparametric Deep Survival Models for Alzheimer's Disease Progression Analysis. - Jacob Thrasher; Kaitlyn Heintzelman; Peter Martone; David Kotlowski; Binod Bhattarai; Donald Adjeroh; Prashnna Gyawali (CoRR, 2026)

Multimodal Federated Learning in Healthcare: A Review. - Jacob Thrasher; Alina Devkota; Prasiddha Siwakoti; Rohit Chivukula; Pranav Poudel; Chuanbo Hu; Ahmad P. Tafti; Binod Bhattarai; Prashnna Gyawali (J. Heal. Informatics Res., 2026)