Anuj Karpatne

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 82

Top Topics

Scientific Discovery

Top Venues

Publications

Medha Sawhney, Bhas Karmarkar, Eric J. Leaman, Arka Daw, Anuj Karpatne, Bahareh Behkam
Motion Enhanced Multi-Level Tracker (MEMTrack): A Deep Learning-Based Approach to Microrobot Tracking in Dense and Low-Contrast Environments. Adv. Intell. Syst. 6 (4) (2024)
Anuj Karpatne, Xiaowei Jia, Vipin Kumar
Knowledge-guided Machine Learning: Current Trends and Future Prospects. CoRR (2024)
Kazi Sajeed Mehrab, M. Maruf, Arka Daw, Harish Babu Manogaran, Abhilash Neog, Mridul Khurana, Bahadir Altintas, Yasin Bakis, Elizabeth G. Campolongo, Matthew J. Thompson, Xiaojun Wang, Hilmar Lapp, Wei-Lun Chao, Paula M. Mabee, Henry L. Bart Jr., Wasila M. Dahdul, Anuj Karpatne
Fish-Vista: A Multi-Purpose Dataset for Understanding & Identification of Traits from Images. CoRR (2024)
Dipanjyoti Paul, Arpita Chowdhury, Xinqi Xiong, Feng-Ju Chang, David Edward Carlyn, Samuel Stevens, Kaiya Provost, Anuj Karpatne, Bryan Carstens, Daniel I. Rubenstein, Charles V. Stewart, Tanya Y. Berger-Wolf, Yu Su, Wei-Lun Chao
A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis. ICLR (2024)
Arka Daw, Jie Bu, Sifan Wang, Paris Perdikaris, Anuj Karpatne
Mitigating Propagation Failures in Physics-informed Neural Networks using Retain-Resample-Release (R3) Sampling. ICML (2023)
Ziyu Yao, Anuj Karpatne
Welcome to AI Matters 9(1). AI Matters 9 (1) (2023)
Ziyu Yao, Anuj Karpatne
Welcome to AI Matters 9(2). AI Matters 9 (2) (2023)
Mohannad Elhamod, Mridul Khurana, Harish Babu Manogaran, Josef C. Uyeda, Meghan A. Balk, Wasila M. Dahdul, Yasin Bakis, Henry L. Bart Jr., Paula M. Mabee, Hilmar Lapp, James P. Balhoff, Caleb Charpentier, David Carlyn, Wei-Lun Chao, Charles V. Stewart, Daniel I. Rubenstein, Tanya Y. Berger-Wolf, Anuj Karpatne
Discovering Novel Biological Traits From Images Using Phylogeny-Guided Neural Networks. KDD (2023)
Mohannad Elhamod, Anuj Karpatne
Neuro-Visualizer: An Auto-encoder-based Loss Landscape Visualization Method. CoRR (2023)
Ziyu Yao, Anuj Karpatne
Welcome to AI Matters 9(3). AI Matters 9 (3) (2023)
Dipanjyoti Paul, Arpita Chowdhury, Xinqi Xiong, Feng-Ju Chang, David Carlyn, Samuel Stevens, Kaiya Provost, Anuj Karpatne, Bryan Carstens, Daniel I. Rubenstein, Charles V. Stewart, Tanya Y. Berger-Wolf, Yu Su, Wei-Lun Chao
A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis. CoRR (2023)
Medha Sawhney, Bhas Karmarkar, Eric J. Leaman, Arka Daw, Anuj Karpatne, Bahareh Behkam
MEMTRACK: A Deep Learning-Based Approach to Microrobot Tracking in Dense and Low-Contrast Environments. CoRR (2023)
Mohannad Elhamod, Mridul Khurana, Harish Babu Manogaran, Josef C. Uyeda, Meghan A. Balk, Wasila M. Dahdul, Yasin Bakis, Henry L. Bart Jr., Paula M. Mabee, Hilmar Lapp, James P. Balhoff, Caleb Charpentier, David Carlyn, Wei-Lun Chao, Charles V. Stewart, Daniel I. Rubenstein, Tanya Y. Berger-Wolf, Anuj Karpatne
Discovering Novel Biological Traits From Images Using Phylogeny-Guided Neural Networks. CoRR (2023)
M. Maruf, Arka Daw, Amartya Dutta, Jie Bu, Anuj Karpatne
Beyond Discriminative Regions: Saliency Maps as Alternatives to CAMs for Weakly Supervised Semantic Segmentation. CoRR (2023)
Jie Bu, Kazi Sajeed Mehrab, Anuj Karpatne
Let There Be Order: Rethinking Ordering in Autoregressive Graph Generation. CoRR (2023)
Sanmay Das, Nicholas Mattei, John P. Dickerson, Sven Koenig, Louise A. Dennis, Larry R. Medsker, Ziyu Yao, Anuj Karpatne, Alan Tsang, Matt Luckcuck
SIGAI Annual Report: July 1 2022 - August 30 2023. AI Matters 9 (3) (2023)
Sanmay Das, Nicholas Mattei, John P. Dickerson, Sven Koenig, Louise A. Dennis, Larry R. Medsker, Ziyu Yao, Anuj Karpatne, Alan Tsang, Matt Luckcuck
SIGAI Annual Report: July 1 2021 - June 30 2022. AI Matters 8 (3) (2022)
Arka Daw, Kyongmin Yeo, Anuj Karpatne, Levente J. Klein
Multi-task Learning for Source Attribution and Field Reconstruction for Methane Monitoring. CoRR (2022)
Arka Daw, Jie Bu, Sifan Wang, Paris Perdikaris, Anuj Karpatne
Rethinking the Importance of Sampling in Physics-informed Neural Networks. CoRR (2022)
Mohannad Elhamod, Jie Bu, Christopher Singh, Matthew Redell, Abantika Ghosh, Viktor Podolskiy, Wei-Cheng Lee, Anuj Karpatne
-PGNN: Learning Physics-guided Neural Networks with Competing Loss Functions for Solving Eigenvalue Problems. ACM Trans. Intell. Syst. Technol. 13 (6) (2022)
Sangeeta Srivastava, Samuel Olin, Viktor Podolskiy, Anuj Karpatne, Wei-Cheng Lee, Anish Arora
Physics-Guided Problem Decomposition for Scaling Deep Learning of High-dimensional Eigen-Solvers: The Case of Schrödinger's Equation. CoRR (2022)
Arka Daw, Kyongmin Yeo, Anuj Karpatne, Levente J. Klein
Multi-task Learning for Source Attribution and Field Reconstruction for Methane Monitoring. Big Data (2022)
Anuj Karpatne, Ziyu Yao
Welcome to AI matters 8(2). AI Matters 8 (2) (2022)
Anuj Karpatne, Ziyu Yao
Welcome to AI matters 8(3). AI Matters 8 (3) (2022)
Anuj Karpatne, Ziyu Yao
Welcome to AI matters 8(4). AI Matters 8 (4) (2022)
Anuj Karpatne, Ziyu Yao
Welcome to AI matters 8(1). AI Matters 8 (1) (2022)
Rose Yu, Paris Perdikaris, Anuj Karpatne
Physics-Guided AI for Large-Scale Spatiotemporal Data. KDD (2021)
Mohannad Elhamod, Jie Bu, Christopher Singh, Matthew Redell, Abantika Ghosh, Viktor Podolskiy, Wei-Cheng Lee, Anuj Karpatne
Learning Physics-guided Neural Networks with Competing Physics Loss: A Summary of Results in Solving Eigenvalue Problems. AAAI Spring Symposium: MLPS (2021)
Iolanda Leite, Anuj Karpatne
Welcome to AI Matters 7(2). AI Matters 7 (2) (2021)
Austin Chennault, Andrey A. Popov, Amit N. Subrahmanya, Rachel Cooper, Anuj Karpatne, Adrian Sandu
Adjoint-Matching Neural Network Surrogates for Fast 4D-Var Data Assimilation. CoRR (2021)
Iolanda Leite, Anuj Karpatne
Welcome to AI matters 7(3). AI Matters 7 (3) (2021)
Arka Daw, M. Maruf, Anuj Karpatne
PID-GAN: A GAN Framework based on a Physics-informed Discriminator for Uncertainty Quantification with Physics. KDD (2021)
Nikhil Muralidhar, Jie Bu, Ze Cao, Neil Raj, Naren Ramakrishnan, Danesh K. Tafti, Anuj Karpatne
PhyFlow: Physics-Guided Deep Learning for Generating Interpretable 3D Flow Fields. ICDM (2021)
Jie Bu, Arka Daw, M. Maruf, Anuj Karpatne
Learning Compact Representations of Neural Networks using DiscriminAtive Masking (DAM). CoRR (2021)
Xiaowei Jia, Jared Willard, Anuj Karpatne, Jordan S. Read, Jacob A. Zwart, Michael S. Steinbach, Vipin Kumar
Physics-Guided Machine Learning for Scientific Discovery: An Application in Simulating Lake Temperature Profiles. Trans. Data Sci. 2 (3) (2021)
Sanmay Das, Nicholas Mattei, John P. Dickerson, Sven Koenig, Louise A. Dennis, Larry R. Medsker, Todd W. Neller, Iolanda Leite, Anuj Karpatne, Alan Tsang
SIGAI annual report: July 1 2020 - June 30 2021. AI Matters 7 (3) (2021)
Jie Bu, Arka Daw, M. Maruf, Anuj Karpatne
Learning Compact Representations of Neural Networks using DiscriminAtive Masking (DAM). NeurIPS (2021)
Reza Sepasdar, Anuj Karpatne, Maryam Shakiba
A Data-Driven Approach to Full-Field Damage and Failure Pattern Prediction in Microstructure-Dependent Composites using Deep Learning. CoRR (2021)
M. Maruf, Anuj Karpatne
Maximizing Cohesion and Separation in Graph Representation Learning: A Distance-aware Negative Sampling Approach. SDM (2021)
Arka Daw, M. Maruf, Anuj Karpatne
PID-GAN: A GAN Framework based on a Physics-informed Discriminator for Uncertainty Quantification with Physics. CoRR (2021)
Jie Bu, Anuj Karpatne
Quadratic Residual Networks: A New Class of Neural Networks for Solving Forward and Inverse Problems in Physics Involving PDEs. SDM (2021)
Iolanda Leite, Anuj Karpatne
Welcome to AI Matters 7(1). AI Matters 7 (1) (2021)
Jie Bu, Anuj Karpatne
Quadratic Residual Networks: A New Class of Neural Networks for Solving Forward and Inverse Problems in Physics Involving PDEs. CoRR (2021)
Ioannis Papakis, Abhijit Sarkar, Anuj Karpatne
A Graph Convolutional Neural Network Based Approach for Traffic Monitoring Using Augmented Detections with Optical Flow. ITSC (2021)
Nikhil Muralidhar, Jie Bu, Ze Cao, Long He, Naren Ramakrishnan, Danesh K. Tafti, Anuj Karpatne
Physics-Guided Deep Learning for Drag Force Prediction in Dense Fluid-Particulate Systems. Big Data 8 (5) (2020)
Jeremy Leipzig, Yasin Bakis, Xiaojun Wang, Mohannad Elhamod, Kelly Diamond, Wasila M. Dahdul, Anuj Karpatne, A. Murat Maga, Paula M. Mabee, Henry L. Bart Jr., Jane Greenberg
Biodiversity Image Quality Metadata Augments Convolutional Neural Network Classification of Fish Species. MTSR (2020)
M. Maruf, Anuj Karpatne
Maximizing Cohesion and Separation in Graph Representation Learning: A Distance-aware Negative Sampling Approach. CoRR (2020)
Ioannis Papakis, Abhijit Sarkar, Anuj Karpatne
GCNNMatch: Graph Convolutional Neural Networks for Multi-Object Tracking via Sinkhorn Normalization. CoRR (2020)
Jie Bu, Mohannad Elhamod, Christopher Singh, Matthew Redell, Wei-Cheng Lee, Anuj Karpatne
Learning Neural Networks with Competing Physics Objectives: An Application in Quantum Mechanics. CoRR (2020)
Arka Daw, R. Quinn Thomas, Cayelan C. Carey, Jordan S. Read, Alison P. Appling, Anuj Karpatne
Physics-Guided Architecture (PGA) of Neural Networks for Quantifying Uncertainty in Lake Temperature Modeling. SDM (2020)
Iolanda Leite, Anuj Karpatne
Welcome to AI matters 6(2). AI Matters 6 (2) (2020)
Iolanda Leite, Anuj Karpatne
Welcome to AI matters 6(3). AI Matters 6 (3) (2020)
Nikhil Muralidhar, Jie Bu, Ze Cao, Long He, Naren Ramakrishnan, Danesh K. Tafti, Anuj Karpatne
PhyNet: Physics Guided Neural Networks for Particle Drag Force Prediction in Assembly. SDM (2020)
Amy McGovern, Iolanda Leite, Anuj Karpatne
Welcome to AI Matters 6(1). AI Matters 6 (1) (2020)
Xiaowei Jia, Jared Willard, Anuj Karpatne, Jordan S. Read, Jacob A. Zwart, Michael S. Steinbach, Vipin Kumar
Process Guided Deep Learning for Modeling Physical Systems: An Application in Lake Temperature Modeling. IGARSS (2020)
Sanmay Das, Nicholas Mattei, John P. Dickerson, Sven Koenig, Louise A. Dennis, Larry R. Medsker, Todd W. Neller, Iolanda Leite, Anuj Karpatne
SIGAI annual report: July 1 2019 - June 30 2020. AI Matters 6 (2) (2020)
Xiaowei Jia, Jared Willard, Anuj Karpatne, Jordan S. Read, Jacob A. Zwart, Michael S. Steinbach, Vipin Kumar
Physics-Guided Machine Learning for Scientific Discovery: An Application in Simulating Lake Temperature Profiles. CoRR (2020)
Xiaowei Jia, Jared Willard, Anuj Karpatne, Jordan S. Read, Jacob Zwart, Michael S. Steinbach, Vipin Kumar
Physics Guided RNNs for Modeling Dynamical Systems: A Case Study in Simulating Lake Temperature Profiles. SDM (2019)
Xiaowei Jia, Guruprasad Nayak, Ankush Khandelwal, Anuj Karpatne, Vipin Kumar
Classifying Heterogeneous Sequential Data by Cyclic Domain Adaptation: An Application in Land Cover Detection. SDM (2019)
Xiaowei Jia, Sheng Li, Ankush Khandelwal, Guruprasad Nayak, Anuj Karpatne, Vipin Kumar
Spatial Context-Aware Networks for Mining Temporal Discriminative Period in Land Cover Detection. SDM (2019)
Arka Daw, R. Quinn Thomas, Cayelan C. Carey, Jordan S. Read, Alison P. Appling, Anuj Karpatne
Physics-Guided Architecture (PGA) of Neural Networks for Quantifying Uncertainty in Lake Temperature Modeling. CoRR (2019)
Anuj Karpatne, Imme Ebert-Uphoff, Sai Ravela, Hassan Ali Babaie, Vipin Kumar
Machine Learning for the Geosciences: Challenges and Opportunities. IEEE Trans. Knowl. Data Eng. 31 (8) (2019)
Nikhil Muralidhar, Jie Bu, Ze Cao, Long He, Naren Ramakrishnan, Danesh K. Tafti, Anuj Karpatne
Physics-guided Design and Learning of Neural Networks for Predicting Drag Force on Particle Suspensions in Moving Fluids. CoRR (2019)
Saurabh Agrawal, Saurabh Verma, Anuj Karpatne, Stefan Liess, Snigdhansu Chatterjee, Vipin Kumar
A Fast-Optimal Guaranteed Algorithm For Learning Sub-Interval Relationships in Time Series. CoRR (2019)
Amy McGovern, Iolanda Leite, Anuj Karpatne
Welcome to AI matters 5(4). AI Matters 5 (4) (2019)
Xiaowei Jia, Mengdie Wang, Ankush Khandelwal, Anuj Karpatne, Vipin Kumar
Recurrent Generative Networks for Multi-Resolution Satellite Data: An Application in Cropland Monitoring. IJCAI (2019)
Gowtham Atluri, Anuj Karpatne, Vipin Kumar
Spatio-Temporal Data Mining: A Survey of Problems and Methods. ACM Comput. Surv. 51 (4) (2018)
Xiaowei Jia, Jared Willard, Anuj Karpatne, Jordan S. Read, Jacob Zwart, Michael S. Steinbach, Vipin Kumar
Physics Guided RNNs for Modeling Dynamical Systems: A Case Study in Simulating Lake Temperature Profiles. CoRR (2018)
Saurabh Agrawal, Saurabh Verma, Gowtham Atluri, Anuj Karpatne, Stefan Liess, Angus W. MacDonald III, Snigdhansu Chatterjee, Vipin Kumar
Mining Sub-Interval Relationships In Time Series Data. CoRR (2018)
Nikhil Muralidhar, Mohammad Raihanul Islam, Manish Marwah, Anuj Karpatne, Naren Ramakrishnan
Incorporating Prior Domain Knowledge into Deep Neural Networks. IEEE BigData (2018)
Xiaowei Jia, Anuj Karpatne, Jared Willard, Michael S. Steinbach, Jordan S. Read, Paul C. Hanson, Hilary A. Dugan, Vipin Kumar
Physics Guided Recurrent Neural Networks For Modeling Dynamical Systems: Application to Monitoring Water Temperature And Quality In Lakes. CoRR (2018)
Anuj Karpatne, William Watkins, Jordan S. Read, Vipin Kumar
Physics-guided Neural Networks (PGNN): An Application in Lake Temperature Modeling. CoRR (2017)
Anuj Karpatne, Imme Ebert-Uphoff, Sai Ravela, Hassan Ali Babaie, Vipin Kumar
Machine Learning for the Geosciences: Challenges and Opportunities. CoRR (2017)
Xiaowei Jia, Ankush Khandelwal, Anuj Karpatne, Vipin Kumar
Discovery of Shifting Patterns in Sequence Classification. CoRR (2017)
Xiaowei Jia, Yifan Hu, Ankush Khandelwal, Anuj Karpatne, Vipin Kumar
Joint sparse auto-encoder: A semi-supervised spatio-temporal approach in mapping large-scale croplands. IEEE BigData (2017)
Anuj Karpatne, Vipin Kumar
Big Data in Climate: Opportunities and Challenges for Machine Learning. KDD (2017)
Gowtham Atluri, Anuj Karpatne, Vipin Kumar
Spatio-Temporal Data Mining: A Survey of Problems and Methods. CoRR (2017)
Anuj Karpatne, Gowtham Atluri, James H. Faghmous, Michael S. Steinbach, Arindam Banerjee, Auroop R. Ganguly, Shashi Shekhar, Nagiza F. Samatova, Vipin Kumar
Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data. IEEE Trans. Knowl. Data Eng. 29 (10) (2017)
Ankush Khandelwal, Anuj Karpatne, Vipin Kumar
ORBIT: Ordering Based Information Transfer Across Space and Time for Global Surface Water Monitoring. CoRR (2017)
Saurabh Agrawal, Gowtham Atluri, Anuj Karpatne, William Haltom, Stefan Liess, Snigdhansu Chatterjee, Vipin Kumar
Tripoles: A New Class of Relationships in Time Series Data. KDD (2017)
Xiaowei Jia, Xi C. Chen, Anuj Karpatne, Vipin Kumar
Identifying dynamic changes with noisy labels in spatial-temporal data: A study on large-scale water monitoring application. IEEE BigData (2016)
Anuj Karpatne, Gowtham Atluri, James H. Faghmous, Michael S. Steinbach, Arindam Banerjee, Auroop R. Ganguly, Shashi Shekhar, Nagiza F. Samatova, Vipin Kumar
Theory-guided Data Science: A New Paradigm for Scientific Discovery. CoRR (2016)
Anuj Karpatne, Stefan Liess
A Guide to Earth Science Data: Summary and Research Challenges. Comput. Sci. Eng. 17 (6) (2015)
Anuj Karpatne, Ankush Khandelwal, Vipin Kumar
Ensemble Learning Methods for Binary Classification with Multi-modality within the Classes. SDM (2015)
Anuj Karpatne, Vipin Kumar
Building Predictive Models for Noisy and Heterogeneous Data: An Application in Global Monitoring of Inland Water Dynamics. ICDM Workshops (2015)
Anuj Karpatne, Vipin Kumar
Adaptive Heterogeneous Ensemble Learning Using the Context of Test Instances. ICDM (2015)
Anuj Karpatne, Ankush Khandelwal, Shyam Boriah, Vipin Kumar
Predictive Learning in the Presence of Heterogeneity and Limited Training Data. SDM (2014)
Reshma Khemchandani, Anuj Karpatne, Suresh Chandra
Proximal support tensor machines. Int. J. Mach. Learn. Cybern. 4 (6) (2013)
Reshma Khemchandani, Anuj Karpatne, Suresh Chandra
Twin support vector regression for the simultaneous learning of a function and its derivatives. Int. J. Mach. Learn. Cybern. 4 (1) (2013)
Xi C. Chen, Anuj Karpatne, Yashu Chamber, Varun Mithal, Michael Lau, Karsten Steinhaeuser, Shyam Boriah, Michael S. Steinbach, Vipin Kumar, Christopher Potter, Steven A. Klooster, Teji Abraham, J. D. Stanley, Juan Carlos Castilla-Rubio
A new data mining framework for forest fire mapping. CIDU (2012)
Anuj Karpatne, Mace Blank, Michael Lau, Shyam Boriah, Karsten Steinhaeuser, Michael S. Steinbach, Vipin Kumar
Importance of vegetation type in forest cover estimation. CIDU (2012)
Reshma Khemchandani, Anuj Karpatne, Suresh Chandra
Generalized eigenvalue proximal support vector regressor. Expert Syst. Appl. 38 (10) (2011)