Measuring movement expertise in surgical tasks. - Kanav Kahol; Narayanan Chatapuram Krishnan; Vineeth Nallure Balasubramanian; Sethuraman Panchanathan; Marshall L. Smith; John Ferrara (ACM Multimedia, 2006)

The role of eye movement signals in dorsal and ventral processing. - John A. Black Jr.; Stuart B. Braiman; Narayanan Chatapuram Krishnan; Sethuraman Panchanathan (Human Vision and Electronic Imaging, 2007)

Detecting and classifying frontal, back and profile views of humans. - Narayanan Chatapuram Krishnan; Baoxin Li; Sethuraman Panchanathan (VISAPP (2), 2007)

A wearable wireless RFID system for accessible shopping environments. - Sreekar Krishna; Vineeth Nallure Balasubramanian; Narayanan Chatapuram Krishnan; Colin Juillard; Terri Hedgpeth; Sethuraman Panchanathan (BODYNETS, 2008)

Analysis of low resolution accelerometer data for continuous human activity recognition. - Narayanan Chatapuram Krishnan; Sethuraman Panchanathan (ICASSP, 2008)

Enriched human-centered multimedia computing through inspirations from disabilities and deficit-centered computing solutions. - Sethuraman Panchanathan; Narayanan Chatapuram Krishnan; Sreekar Krishna; Troy McDaniel; Vineeth Nallure Balasubramanian (HCC, 2008)

Recognizing short duration hand movements from accelerometer data. - Narayanan Chatapuram Krishnan; Gaurav N. Pradhan; Sethuraman Panchanathan (ICME, 2009)

Recognition of hand movements using wearable accelerometers. - Narayanan Chatapuram Krishnan; Colin Juillard; Dirk Colbry; Sethuraman Panchanathan (J. Ambient Intell. Smart Environ., 2009)

Activity gesture spotting using a threshold model based on Adaptive Boosting. - Narayanan Chatapuram Krishnan; Prasanth Lade; Sethuraman Panchanathan (ICME, 2010)

Task Prediction in Cooking Activities Using Hierarchical State Space Markov Chain and Object Based Task Grouping. - Prasanth Lade; Narayanan Chatapuram Krishnan; Sethuraman Panchanathan (ISM, 2010)

A computational framework for wearable accelerometer based activity and gesture recognition. - Narayanan Chatapuram Krishnan (2010)

Defining the Complexity of an Activity. - Yasamin Sahaf; Narayanan Chatapuram Krishnan; Diane J. Cook (Activity Context Representation, 2011)

Topology Preserving Domain Adaptation for Addressing Subject Based Variability in SEMG Signal. - Rita Chattopadhyay; Narayanan Chatapuram Krishnan; Sethuraman Panchanathan (AAAI Spring Symposium: Computational Physiology, 2011)

Hierarchical domain adaptation for SEMG signal classification across multiple subjects. - Rita Chattopadhyay; Narayanan Chatapuram Krishnan; Sethuraman Panchanathan (EMBC, 2011)

Preface. - Diane J. Cook; Narayanan Chatapuram Krishnan; Parisa Rashidi; Marjorie Skubic; Alex Mihailidis (AAAI Fall Symposium: Artificial Intelligence for Gerontechnology, 2012)

Simple and Complex Activity Recognition through Smart Phones. - Stefan Dernbach; Barnan Das; Narayanan Chatapuram Krishnan; Brian L. Thomas; Diane J. Cook (Intelligent Environments, 2012)

Automated Activity Interventions to Assist with Activities of Daily Living. - Barnan Das; Narayanan Chatapuram Krishnan; Diane J. Cook (Agents and Ambient Intelligence, 2012)

wRACOG: A Gibbs Sampling-Based Oversampling Technique. - Barnan Das; Narayanan Chatapuram Krishnan; Diane J. Cook (ICDM, 2013)

Handling Class Overlap and Imbalance to Detect Prompt Situations in Smart Homes. - Barnan Das; Narayanan Chatapuram Krishnan; Diane J. Cook (ICDM Workshops, 2013)

Reports on the 2012 AAAI Fall Symposium Series. - Rezarta Islamaj Dogan; Yolanda Gil; Haym Hirsh; Narayanan Chatapuram Krishnan; Michael Lewis 001; Çetin Meriçli; Parisa Rashidi; Victor Raskin; Samarth Swarup; Wei Sun; Julia M. Taylor; Lana Yeganova (AI Mag., 2013)

CASAS: A Smart Home in a Box. - Diane J. Cook; Aaron S. Crandall; Brian L. Thomas; Narayanan Chatapuram Krishnan (Computer, 2013)

Learning a taxonomy of predefined and discovered activity patterns. - Narayanan Chatapuram Krishnan; Diane J. Cook; Zachary Wemlinger (J. Ambient Intell. Smart Environ., 2013)

Transfer learning for activity recognition: a survey. - Diane J. Cook; Kyle D. Feuz; Narayanan Chatapuram Krishnan (Knowl. Inf. Syst., 2013)

Activity Discovery and Activity Recognition: A New Partnership. - Diane J. Cook; Narayanan Chatapuram Krishnan; Parisa Rashidi (IEEE Trans. Cybern., 2013)

Mining the home environment. - Diane J. Cook; Narayanan Chatapuram Krishnan (J. Intell. Inf. Syst., 2014)

Activity recognition on streaming sensor data. - Narayanan Chatapuram Krishnan; Diane J. Cook (Pervasive Mob. Comput., 2014)

Multi-label Learning for Activity Recognition. - Rahul Kumar; Imroj Qamar; Jaskaran Singh Virdi; Narayanan Chatapuram Krishnan (Intelligent Environments, 2015)

RACOG and wRACOG: Two Probabilistic Oversampling Techniques. - Barnan Das; Narayanan Chatapuram Krishnan; Diane J. Cook (IEEE Trans. Knowl. Data Eng., 2015)

SpotGarbage: smartphone app to detect garbage using deep learning. - Gaurav Mittal; Kaushal B. Yagnik; Mohit Garg; Narayanan C. Krishnan (UbiComp, 2016)

Supervised deep segmentation network for brain extraction. - Apoorva Sikka; Gaurav Mittal; Deepti R. Bathula; Narayanan C. Krishnan (ICVGIP, 2016)

Supervised Heterogeneous Domain Adaptation via Random Forests. - Sanatan Sukhija; Narayanan Chatapuram Krishnan; Gurkanwal Singh (IJCAI, 2016)

One-Class Classification-Based Real-Time Activity Error Detection in Smart Homes. - Barnan Das; Diane J. Cook; Narayanan Chatapuram Krishnan; Maureen Schmitter-Edgecombe (IEEE J. Sel. Top. Signal Process., 2016)

Multi-Task Deep Learning for Predicting Poverty From Satellite Images. - Shailesh M. Pandey; Tushar Agarwal; Narayanan C. Krishnan (AAAI, 2018)

Supervised heterogeneous transfer learning using random forests. - Sanatan Sukhija; Narayanan Chatapuram Krishnan; Deepak Kumar (COMAD/CODS, 2018)

Deep Cross Modal Learning for Caricature Verification and Identification (CaVINet). - Jatin Garg; Skand Vishwanath Peri; Himanshu Tolani; Narayanan C. Krishnan (ACM Multimedia, 2018)

Web-Induced Heterogeneous Transfer Learning with Sample Selection. - Sanatan Sukhija; Narayanan Chatapuram Krishnan (ECML/PKDD (2), 2018)

Semantically Aligned Bias Reducing Zero Shot Learning. - Akanksha Paul; Narayanan C. Krishnan; Prateek Munjal (CVPR, 2019)

Supervised heterogeneous feature transfer via random forests. - Sanatan Sukhija; Narayanan Chatapuram Krishnan (Artif. Intell., 2019)

Implicit Discriminator in Variational Autoencoder. - Prateek Munjal; Akanksha Paul; Narayanan C. Krishnan (IJCNN, 2020)

Multi-Partition Feature Alignment Network for Unsupervised Domain Adaptation. - Sanatan Sukhija; Srenivas Varadarajan; Narayanan C. Krishnan; Sujit Rai (IJCNN, 2020)

Wheat Crop Yield Prediction Using Deep LSTM Model. - Sagarika Sharma; Sujit Rai; Narayanan C. Krishnan (CoRR, 2020)

Stress Testing of Meta-learning Approaches for Few-shot Learning. - Aroof Aimen; Sahil Sidheekh; Vineet Madan; Narayanan C. Krishnan (MetaDL@AAAI, 2021)

MAIRE - A Model-Agnostic Interpretable Rule Extraction Procedure for Explaining Classifiers. - Rajat Sharma; Nikhil Reddy; Vidhya Kamakshi; Narayanan C. Krishnan; Shweta Jain 002 (CD-MAKE, 2021)

Pho(SC)Net: An Approach Towards Zero-Shot Word Image Recognition in Historical Documents. - Anuj Rai; Narayanan C. Krishnan; Sukalpa Chanda (ICDAR (1), 2021)

On Characterizing GAN Convergence Through Proximal Duality Gap. - Sahil Sidheekh; Aroof Aimen; Narayanan C. Krishnan (ICML, 2021)

PACE: Posthoc Architecture-Agnostic Concept Extractor for Explaining CNNs. - Vidhya Kamakshi; Uday Gupta; Narayanan C. Krishnan (IJCNN, 2021)

On Duality Gap as a Measure for Monitoring GAN Training. - Sahil Sidheekh; Aroof Aimen; Vineet Madan; Narayanan C. Krishnan (IJCNN, 2021)

Task Attended Meta-Learning for Few-Shot Learning. - Aroof Aimen; Sahil Sidheekh; Narayanan C. Krishnan (CoRR, 2021)

Evaluation of Saliency-based Explainability Method. - Sam Zabdiel Sunder Samuel; Vidhya Kamakshi; Namrata Lodhi; Narayanan C. Krishnan (CoRR, 2021)

Deep Geospatial Interpolation Networks. - Sumit Kumar Varshney; Jeetu Kumar; Aditya Tiwari; Rishabh Singh; Venkata M. V. Gunturi; Narayanan C. Krishnan (CoRR, 2021)

Efficient Algorithms For Fair Clustering with a New Fairness Notion. - Shivam Gupta 004; Ganesh Ghalme; Narayanan C. Krishnan; Shweta Jain 002 (CoRR, 2021)

MACE: Model Agnostic Concept Extractor for Explaining Image Classification Networks. - Ashish Kumar; Karan Sehgal; Prerna Garg; Vidhya Kamakshi; Narayanan Chatapuram Krishnan (IEEE Trans. Artif. Intell., 2021)

Explainable Supervised Domain Adaptation. - Vidhya Kamakshi; Narayanan C. Krishnan (IJCNN, 2022)

Towards Reducing Aleatoric Uncertainty for Medical Imaging Tasks. - Abhishek Singh Sambyal; Narayanan C. Krishnan; Deepti R. Bathula (ISBI, 2022)

Adversarial Projections to Tackle Support-Query Shifts in Few-Shot Meta-Learning. - Aroof Aimen; Bharat Ladrecha; Narayanan C. Krishnan (ECML/PKDD (3), 2022)

Group Fair Clustering Revisited - Notions and Efficient Algorithm. - Shivam Gupta 004; Ganesh Ghalme; Narayanan C. Krishnan; Shweta Jain 002 (AAMAS, 2023)

Algorithmic Recourse based on User's Feature-order Preference. - Manan Singh; Sai Srinivas Kancheti; Shivam Gupta 004; Ganesh Ghalme; Shweta Jain 002; Narayanan C. Krishnan (COMAD/CODS, 2023)

ResPho(SC)Net: A Zero-Shot Learning Framework for Norwegian Handwritten Word Image Recognition. - Aniket Gurav; Joakim Jensen; Narayanan C. Krishnan; Sukalpa Chanda (IbPRIA, 2023)

Pho(SC)-CTC - a hybrid approach towards zero-shot word image recognition. - Ravi Bhatt; Anuj Rai; Sukalpa Chanda; Narayanan C. Krishnan (Int. J. Document Anal. Recognit., 2023)

Efficient algorithms for fair clustering with a new notion of fairness. - Shivam Gupta 004; Ganesh Ghalme; Narayanan C. Krishnan; Shweta Jain 002 (Data Min. Knowl. Discov., 2023)

Leveraging Task Variability in Meta-learning. - Aroof Aimen; Bharat Ladrecha; Sahil Sidheekh; Narayanan C. Krishnan (SN Comput. Sci., 2023)

Understanding calibration of deep neural networks for medical image classification. - Abhishek Singh Sambyal; Usma Niyaz; Narayanan C. Krishnan; Deepti R. Bathula (Comput. Methods Programs Biomed., 2023)

Online Algorithm for Clustering with Capacity Constraints. - Shivam Gupta 004; Shweta Jain 002; Narayanan C. Krishnan; Ganesh Ghalme; Nandyala Hemachandra (COMAD/CODS, 2024)

SCE: Shared Concept Extractor to Explain a CNN's Classification Dynamics. - Vidhya Kamakshi; Narayanan C. Krishnan (COMAD/CODS, 2024)

Expanding the Image Embedding Space for Language-Free Text-to-Face Image Generation. - Joakim Jensen; Sukalpa Chanda; Narayanan C. Krishnan; David S. Doermann (GCPR (2), 2024)

Capacitated Online Clustering Algorithm. - Shivam Gupta 004; Shweta Jain 002; Narayanan C. Krishnan; Ganesh Ghalme; Nandyala Hemachandra (ECAI, 2024)

Word-Diffusion: Diffusion-Based Handwritten Text Word Image Generation. - Aniket Gurav; Narayanan C. Krishnan; Sukalpa Chanda (ICPR (19), 2024)

HTLDIFF: Handwritten Text Line Generation - A Diffusion Model Perspective. - Aniket Gurav; Sukalpa Chanda; Narayanan C. Krishnan (IPTA, 2024)

LS+: Informed Label Smoothing for Improving Calibration in Medical Image Classification. - Abhishek Singh Sambyal; Usma Niyaz; Saksham Shrivastava; Narayanan C. Krishnan; Deepti R. Bathula (MICCAI (10), 2024)

Adaptation: Blessing or Curse for Higher Way Meta-Learning. - Aroof Aimen; Sahil Sidheekh; Bharat Ladrecha; Hansin Ahuja; Narayanan C. Krishnan (IEEE Trans. Artif. Intell., 2024)

Generalized Cross-Domain Multi-Label Few-Shot Learning for Chest X-Rays. - Aroof Aimen; Arsh Verma; Makarand Tapaswi; Narayanan C. Krishnan (ISBI, 2025)

Scene text recognition: an Indic perspective. - Vasanthan P. Vijayan; Sukalpa Chanda; David S. Doermann; Narayanan C. Krishnan (Int. J. Document Anal. Recognit., 2025)

Tractable Sharpness-Aware Learning of Probabilistic Circuits. - Hrithik Suresh; Sahil Sidheekh; Vishnu Shreeram M. P; Sriraam Natarajan; Narayanan C. Krishnan (CoRR, 2025)