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ORCIDNarayanan Chatapuram Krishnan
Narayanan C. Krishnan
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- affiliation: Indian Institute of Technology Ropar
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2020 – today
- 2024
[j17]Aroof Aimen
, Sahil Sidheekh, Bharat Ladrecha, Hansin Ahuja, Narayanan C. Krishnan:
Adaptation: Blessing or Curse for Higher Way Meta-Learning. IEEE Trans. Artif. Intell. 5(4): 1844-1856 (2024)- [c43]Vidhya Kamakshi, Narayanan C. Krishnan:
SCE: Shared Concept Extractor to Explain a CNN's Classification Dynamics. COMAD/CODS 2024: 109-117 - [c42]Shivam Gupta, Shweta Jain, Narayanan C. Krishnan, Ganesh Ghalme, Nandyala Hemachandra:
Online Algorithm for Clustering with Capacity Constraints. COMAD/CODS 2024: 572-573 - [c41]Shivam Gupta, Shweta Jain, Narayanan C. Krishnan, Ganesh Ghalme, Nandyala Hemachandra:
Capacitated Online Clustering Algorithm. ECAI 2024: 1880-1887 - [c40]Abhishek Singh Sambyal, Usma Niyaz, Saksham Shrivastava, Narayanan C. Krishnan, Deepti R. Bathula:
LS+: Informed Label Smoothing for Improving Calibration in Medical Image Classification. MICCAI (10) 2024: 513-523 - 2023
- [j16]Abhishek Singh Sambyal, Usma Niyaz, Narayanan C. Krishnan, Deepti R. Bathula:
Understanding calibration of deep neural networks for medical image classification. Comput. Methods Programs Biomed. 242: 107816 (2023) - [j15]Shivam Gupta, Ganesh Ghalme, Narayanan C. Krishnan, Shweta Jain:
Efficient algorithms for fair clustering with a new notion of fairness. Data Min. Knowl. Discov. 37(5): 1959-1997 (2023) - [j14]Ravi Bhatt, Anuj Rai, Sukalpa Chanda, Narayanan C. Krishnan:
Pho(SC)-CTC - a hybrid approach towards zero-shot word image recognition. Int. J. Document Anal. Recognit. 26(1): 51-63 (2023) - [j13]Aroof Aimen, Bharat Ladrecha, Sahil Sidheekh, Narayanan C. Krishnan:
Leveraging Task Variability in Meta-learning. SN Comput. Sci. 4(5): 539 (2023) - [c39]Shivam Gupta, Ganesh Ghalme, Narayanan C. Krishnan, Shweta Jain:
Group Fair Clustering Revisited - Notions and Efficient Algorithm. AAMAS 2023: 2854-2856 - [c38]Manan Singh, Sai Srinivas Kancheti, Shivam Gupta, Ganesh Ghalme, Shweta Jain, Narayanan C. Krishnan:
Algorithmic Recourse based on User's Feature-order Preference. COMAD/CODS 2023: 293-294 - [c37]Aniket Gurav, Joakim Jensen, Narayanan C. Krishnan, Sukalpa Chanda:
ResPho(SC)Net: A Zero-Shot Learning Framework for Norwegian Handwritten Word Image Recognition. IbPRIA 2023: 182-196 - [i18]Aroof Aimen, Arsh Verma, Makarand Tapaswi, Narayanan C. Krishnan:
Generalized Cross-domain Multi-label Few-shot Learning for Chest X-rays. CoRR abs/2309.04462 (2023) - [i17]Abhishek Singh Sambyal, Usma Niyaz, Narayanan C. Krishnan, Deepti R. Bathula:
Understanding Calibration of Deep Neural Networks for Medical Image Classification. CoRR abs/2309.13132 (2023) - 2022
- [c36]Vidhya Kamakshi, Narayanan C. Krishnan:
Explainable Supervised Domain Adaptation. IJCNN 2022: 1-8 - [c35]Abhishek Singh Sambyal, Narayanan C. Krishnan, Deepti R. Bathula:
Towards Reducing Aleatoric Uncertainty for Medical Imaging Tasks. ISBI 2022: 1-4 - [c34]Aroof Aimen, Bharat Ladrecha, Narayanan C. Krishnan:
Adversarial Projections to Tackle Support-Query Shifts in Few-Shot Meta-Learning. ECML/PKDD (3) 2022: 615-630 - 2021
- [j12]Ashish Kumar, Karan Sehgal, Prerna Garg, Vidhya Kamakshi, Narayanan Chatapuram Krishnan:
MACE: Model Agnostic Concept Extractor for Explaining Image Classification Networks. IEEE Trans. Artif. Intell. 2(6): 574-583 (2021) - [c33]Aroof Aimen, Sahil Sidheekh, Vineet Madan, Narayanan C. Krishnan:
Stress Testing of Meta-learning Approaches for Few-shot Learning. MetaDL@AAAI 2021: 38-44 - [c32]Rajat Sharma, Nikhil Reddy, Vidhya Kamakshi, Narayanan C. Krishnan, Shweta Jain:
MAIRE - A Model-Agnostic Interpretable Rule Extraction Procedure for Explaining Classifiers. CD-MAKE 2021: 329-349 - [c31]Anuj Rai, Narayanan C. Krishnan, Sukalpa Chanda:
Pho(SC)Net: An Approach Towards Zero-Shot Word Image Recognition in Historical Documents. ICDAR (1) 2021: 19-33 - [c30]Sahil Sidheekh, Aroof Aimen, Narayanan C. Krishnan:
On Characterizing GAN Convergence Through Proximal Duality Gap. ICML 2021: 9660-9670 - [c29]Vidhya Kamakshi, Uday Gupta, Narayanan C. Krishnan:
PACE: Posthoc Architecture-Agnostic Concept Extractor for Explaining CNNs. IJCNN 2021: 1-8 - [c28]Sahil Sidheekh, Aroof Aimen, Vineet Madan, Narayanan C. Krishnan:
On Duality Gap as a Measure for Monitoring GAN Training. IJCNN 2021: 1-8 - [i16]Aroof Aimen, Sahil Sidheekh, Vineet Madan, Narayanan C. Krishnan:
Stress Testing of Meta-learning Approaches for Few-shot Learning. CoRR abs/2101.08587 (2021) - [i15]Sahil Sidheekh, Aroof Aimen, Narayanan C. Krishnan:
Characterizing GAN Convergence Through Proximal Duality Gap. CoRR abs/2105.04801 (2021) - [i14]Anuj Rai, Narayanan C. Krishnan, Sukalpa Chanda:
Pho(SC)Net: An Approach Towards Zero-shot Word Image Recognition in Historical Documents. CoRR abs/2105.15093 (2021) - [i13]Aroof Aimen, Sahil Sidheekh, Narayanan C. Krishnan:
Task Attended Meta-Learning for Few-Shot Learning. CoRR abs/2106.10642 (2021) - [i12]Sam Zabdiel Sunder Samuel, Vidhya Kamakshi, Namrata Lodhi, Narayanan C. Krishnan:
Evaluation of Saliency-based Explainability Method. CoRR abs/2106.12773 (2021) - [i11]Sumit Kumar Varshney, Jeetu Kumar, Aditya Tiwari, Rishabh Singh, Venkata M. V. Gunturi, Narayanan C. Krishnan:
Deep Geospatial Interpolation Networks. CoRR abs/2108.06670 (2021) - [i10]Vidhya Kamakshi, Uday Gupta, Narayanan C. Krishnan:
PACE: Posthoc Architecture-Agnostic Concept Extractor for Explaining CNNs. CoRR abs/2108.13828 (2021) - [i9]Shivam Gupta, Ganesh Ghalme, Narayanan C. Krishnan, Shweta Jain:
Efficient Algorithms For Fair Clustering with a New Fairness Notion. CoRR abs/2109.00708 (2021) - [i8]Abhishek Singh Sambyal, Narayanan C. Krishnan, Deepti R. Bathula:
Towards Reducing Aleatoric Uncertainty for Medical Imaging Tasks. CoRR abs/2110.11012 (2021) - 2020
- [c27]Prateek Munjal, Akanksha Paul, Narayanan C. Krishnan:
Implicit Discriminator in Variational Autoencoder. IJCNN 2020: 1-8 - [c26]Sanatan Sukhija, Srenivas Varadarajan, Narayanan C. Krishnan, Sujit Rai:
Multi-Partition Feature Alignment Network for Unsupervised Domain Adaptation. IJCNN 2020: 1-8 - [i7]Ashish Kumar, Karan Sehgal, Prerna Garg, Vidhya Kamakshi, Narayanan C. Krishnan:
MACE: Model Agnostic Concept Extractor for Explaining Image Classification Networks. CoRR abs/2011.01472 (2020) - [i6]Sagarika Sharma, Sujit Rai, Narayanan C. Krishnan:
Wheat Crop Yield Prediction Using Deep LSTM Model. CoRR abs/2011.01498 (2020) - [i5]Rajat Sharma, Nikhil Reddy, Vidhya Kamakshi, Narayanan C. Krishnan, Shweta Jain:
MAIRE - A Model-Agnostic Interpretable Rule Extraction Procedure for Explaining Classifiers. CoRR abs/2011.01506 (2020) - [i4]Sahil Sidheekh, Aroof Aimen, Vineet Madan, Narayanan C. Krishnan:
On Duality Gap as a Measure for Monitoring GAN Training. CoRR abs/2012.06723 (2020)
2010 – 2019
- 2019
- [j11]Sanatan Sukhija, Narayanan Chatapuram Krishnan:
Supervised heterogeneous feature transfer via random forests. Artif. Intell. 268: 30-53 (2019) - [c25]Akanksha Paul, Narayanan C. Krishnan, Prateek Munjal:
Semantically Aligned Bias Reducing Zero Shot Learning. CVPR 2019: 7056-7065 - [i3]Akanksha Paul, Narayanan C. Krishnan, Prateek Munjal:
Semantically Aligned Bias Reducing Zero Shot Learning. CoRR abs/1904.07659 (2019) - [i2]Prateek Munjal, Akanksha Paul, Narayanan C. Krishnan:
Implicit Discriminator in Variational Autoencoder. CoRR abs/1909.13062 (2019) - 2018
- [c24]Shailesh M. Pandey, Tushar Agarwal, Narayanan C. Krishnan:
Multi-Task Deep Learning for Predicting Poverty From Satellite Images. AAAI 2018: 7793-7798 - [c23]Sanatan Sukhija, Narayanan Chatapuram Krishnan, Deepak Kumar:
Supervised heterogeneous transfer learning using random forests. COMAD/CODS 2018: 157-166 - [c22]Jatin Garg, Skand Vishwanath Peri, Himanshu Tolani, Narayanan C. Krishnan:
Deep Cross Modal Learning for Caricature Verification and Identification (CaVINet). ACM Multimedia 2018: 1101-1109 - [c21]Sanatan Sukhija, Narayanan Chatapuram Krishnan:
Web-Induced Heterogeneous Transfer Learning with Sample Selection. ECML/PKDD (2) 2018: 777-793 - [i1]Jatin Garg, Skand Vishwanath Peri, Himanshu Tolani, Narayanan C. Krishnan:
Deep Cross Modal Learning for Caricature Verification and Identification(CaVINet). CoRR abs/1807.11688 (2018) - 2016
- [j10]Barnan Das, Diane J. Cook, Narayanan Chatapuram Krishnan, Maureen Schmitter-Edgecombe:
One-Class Classification-Based Real-Time Activity Error Detection in Smart Homes. IEEE J. Sel. Top. Signal Process. 10(5): 914-923 (2016) - [c20]Gaurav Mittal, Kaushal B. Yagnik, Mohit Garg, Narayanan C. Krishnan:
SpotGarbage: smartphone app to detect garbage using deep learning. UbiComp 2016: 940-945 - [c19]Apoorva Sikka, Gaurav Mittal, Deepti R. Bathula, Narayanan C. Krishnan:
Supervised deep segmentation network for brain extraction. ICVGIP 2016: 9:1-9:8 - [c18]Sanatan Sukhija, Narayanan Chatapuram Krishnan, Gurkanwal Singh:
Supervised Heterogeneous Domain Adaptation via Random Forests. IJCAI 2016: 2039-2045 - 2015
- [j9]Barnan Das, Narayanan Chatapuram Krishnan, Diane J. Cook:
RACOG and wRACOG: Two Probabilistic Oversampling Techniques. IEEE Trans. Knowl. Data Eng. 27(1): 222-234 (2015) - [c17]Rahul Kumar, Imroj Qamar, Jaskaran Singh Virdi, Narayanan Chatapuram Krishnan:
Multi-label Learning for Activity Recognition. Intelligent Environments 2015: 152-155 - 2014
- [j8]Diane J. Cook, Narayanan Chatapuram Krishnan:
Mining the home environment. J. Intell. Inf. Syst. 43(3): 503-519 (2014) - [j7]Narayanan Chatapuram Krishnan, Diane J. Cook:
Activity recognition on streaming sensor data. Pervasive Mob. Comput. 10: 138-154 (2014) - 2013
- [j6]Rezarta Islamaj Dogan, Yolanda Gil, Haym Hirsh, Narayanan Chatapuram Krishnan, Michael Lewis, Çetin Meriçli, Parisa Rashidi, Victor Raskin, Samarth Swarup, Wei Sun, Julia M. Taylor, Lana Yeganova:
Reports on the 2012 AAAI Fall Symposium Series. AI Mag. 34(1): 93-100 (2013) - [j5]Diane J. Cook, Aaron S. Crandall, Brian L. Thomas, Narayanan Chatapuram Krishnan:
CASAS: A Smart Home in a Box. Computer 46(7): 62-69 (2013) - [j4]Narayanan Chatapuram Krishnan, Diane J. Cook, Zachary Wemlinger:
Learning a taxonomy of predefined and discovered activity patterns. J. Ambient Intell. Smart Environ. 5(6): 621-637 (2013) - [j3]Diane J. Cook, Kyle D. Feuz, Narayanan Chatapuram Krishnan:
Transfer learning for activity recognition: a survey. Knowl. Inf. Syst. 36(3): 537-556 (2013) - [j2]Diane J. Cook, Narayanan Chatapuram Krishnan, Parisa Rashidi:
Activity Discovery and Activity Recognition: A New Partnership. IEEE Trans. Cybern. 43(3): 820-828 (2013) - [c16]Barnan Das, Narayanan Chatapuram Krishnan, Diane J. Cook:
wRACOG: A Gibbs Sampling-Based Oversampling Technique. ICDM 2013: 111-120 - [c15]Barnan Das, Narayanan Chatapuram Krishnan, Diane J. Cook:
Handling Class Overlap and Imbalance to Detect Prompt Situations in Smart Homes. ICDM Workshops 2013: 266-273 - 2012
- [c14]Diane J. Cook, Narayanan Chatapuram Krishnan, Parisa Rashidi, Marjorie Skubic, Alex Mihailidis:
Preface. AAAI Fall Symposium: Artificial Intelligence for Gerontechnology 2012 - [c13]Stefan Dernbach, Barnan Das, Narayanan Chatapuram Krishnan, Brian L. Thomas, Diane J. Cook:
Simple and Complex Activity Recognition through Smart Phones. Intelligent Environments 2012: 214-221 - [p1]Barnan Das, Narayanan Chatapuram Krishnan, Diane J. Cook:
Automated Activity Interventions to Assist with Activities of Daily Living. Agents and Ambient Intelligence 2012: 137-158 - 2011
- [c12]Yasamin Sahaf, Narayanan Chatapuram Krishnan, Diane J. Cook:
Defining the Complexity of an Activity. Activity Context Representation 2011 - [c11]Rita Chattopadhyay, Narayanan Chatapuram Krishnan, Sethuraman Panchanathan:
Topology Preserving Domain Adaptation for Addressing Subject Based Variability in SEMG Signal. AAAI Spring Symposium: Computational Physiology 2011 - [c10]Rita Chattopadhyay, Narayanan Chatapuram Krishnan, Sethuraman Panchanathan:
Hierarchical domain adaptation for SEMG signal classification across multiple subjects. EMBC 2011: 7853-7856 - 2010
- [b1]Narayanan Chatapuram Krishnan:
A computational framework for wearable accelerometer based activity and gesture recognition. Arizona State University, Tempe, USA, 2010 - [c9]Narayanan Chatapuram Krishnan, Prasanth Lade, Sethuraman Panchanathan:
Activity gesture spotting using a threshold model based on Adaptive Boosting. ICME 2010: 155-160 - [c8]Prasanth Lade, Narayanan Chatapuram Krishnan, Sethuraman Panchanathan:
Task Prediction in Cooking Activities Using Hierarchical State Space Markov Chain and Object Based Task Grouping. ISM 2010: 284-289
2000 – 2009
- 2009
- [j1]Narayanan Chatapuram Krishnan, Colin Juillard, Dirk Colbry, Sethuraman Panchanathan:
Recognition of hand movements using wearable accelerometers. J. Ambient Intell. Smart Environ. 1(2): 143-155 (2009) - [c7]Narayanan Chatapuram Krishnan, Gaurav N. Pradhan, Sethuraman Panchanathan:
Recognizing short duration hand movements from accelerometer data. ICME 2009: 1700-1703 - 2008
- [c6]Sreekar Krishna, Vineeth Nallure Balasubramanian, Narayanan Chatapuram Krishnan, Colin Juillard, Terri Hedgpeth, Sethuraman Panchanathan:
A wearable wireless RFID system for accessible shopping environments. BODYNETS 2008: 29 - [c5]Narayanan Chatapuram Krishnan, Sethuraman Panchanathan:
Analysis of low resolution accelerometer data for continuous human activity recognition. ICASSP 2008: 3337-3340 - [c4]Sethuraman Panchanathan, Narayanan Chatapuram Krishnan, Sreekar Krishna, Troy McDaniel, Vineeth Nallure Balasubramanian:
Enriched human-centered multimedia computing through inspirations from disabilities and deficit-centered computing solutions. HCC 2008: 35-42 - 2007
- [c3]John A. Black Jr., Stuart B. Braiman, Narayanan Chatapuram Krishnan, Sethuraman Panchanathan:
The role of eye movement signals in dorsal and ventral processing. Human Vision and Electronic Imaging 2007: 649215 - [c2]Narayanan Chatapuram Krishnan, Baoxin Li, Sethuraman Panchanathan:
Detecting and classifying frontal, back and profile views of humans. VISAPP (2) 2007: 137-142 - 2006
- [c1]Kanav Kahol, Narayanan Chatapuram Krishnan, Vineeth Nallure Balasubramanian, Sethuraman Panchanathan, Marshall L. Smith, John Ferrara:
Measuring movement expertise in surgical tasks. ACM Multimedia 2006: 719-722
Coauthor Index
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