A. Karpatne

发表

Physics Guided RNNs for Modeling Dynamical Systems: A Case Study in Simulating Lake Temperature Profiles

Anuj Karpatne, Vipin Kumar, Michael S. Steinbach, 2018, SDM.

Machine Learning for the Geosciences: Challenges and Opportunities

Anuj Karpatne, Vipin Kumar, Imme Ebert-Uphoff, 2017, IEEE Transactions on Knowledge and Data Engineering.

An approach for global monitoring of surface water extent variations in reservoirs using MODIS data

A. Karpatne, Vipin Kumar, D. Lettenmaier, 2017 .

Global Monitoring of Inland Water Dynamics: State-of-the-Art, Challenges, and Opportunities

Xi Chen, Anuj Karpatne, Vipin Kumar, 2016, Computational Sustainability.

A Data-Driven Approach to Full-Field Damage and Failure Pattern Prediction in Microstructure-Dependent Composites using Deep Learning pdf

Anuj Karpatne, Reza Sepasdar, Maryam Shakiba, 2021, ArXiv.

Welcome to AI Matters 7(2)

Anuj Karpatne, Iolanda Leite, A. Karpatne, 2021, AI Matters.

Physics-Guided Machine Learning for Scientific Discovery: An Application in Simulating Lake Temperature Profiles pdf

Anuj Karpatne, Xiaowei Jia, Vipin Kumar, 2020, Trans. Data Sci..

Predicting lake surface water phosphorus dynamics using process-guided machine learning

X. Jia, A. Karpatne, J. Read, 2020, Ecological Modelling.

BHPMF – a hierarchical Bayesian approach to gap-filling and trait prediction for macroecology and functional biogeography

Anuj Karpatne, Markus Reichstein, Sandra Lavorel, 2015 .

Process‐Guided Deep Learning Predictions of Lake Water Temperature

Anuj Karpatne, Xiaowei Jia, Jordan S. Read, 2019, Water Resources Research.

Spatio-Temporal Data Mining: A Survey of Problems and Methods

A. Karpatne, Vipin Kumar, G. Atluri, 2017, ArXiv.

Machine learning as an inversion algorithm for aerosol profile and property retrieval from multi-axis differential absorption spectroscopy measurements: a feasibility study

A. Karpatne, E. Spinei, Yunsheng Dong, 2019 .

Global Lake Monitoring using Group-specific Local Learning

A. Karpatne, 2014 .

GCNNMatch: Graph Convolutional Neural Networks for Multi-Object Tracking via Sinkhorn Normalization

A. Karpatne, Abhijit Sarkar, Ioannis Papakis, 2020, arXiv.org.

Emerging Data Science and Machine Learning Opportunities in the Weather and Climate Sciences

Karthik Kashinath, Anuj Karpatne, Kevin A. Reed, 2018 .

New Algorithms for Detecting Forest Fires on a Global Scale 1 From MODIS Time Series Analysis

Xi C. Chen, A. Karpatne, M. Steinbach, 2012 .

A Data Mining Framework for Forest Fire Mapping

Xi C. Chen, A. Karpatne, M. Steinbach, 2012 .

A data-driven approach to full-field nonlinear stress distribution and failure pattern prediction in composites using deep learning

A. Karpatne, R. Sepasdar, M. Shakiba, 2022, Computer Methods in Applied Mechanics and Engineering.

Exploratory analysis of machine learning methods in predicting subsurface temperature and geothermal gradient of Northeastern United States

A. Karpatne, Seho Lee, Bahareh Nojabaei, 2021, Geothermal Energy.

Rethinking the Importance of Sampling in Physics-informed Neural Networks

A. Karpatne, P. Perdikaris, Sifan Wang, 2022, ArXiv.

Deep Learning Methods in Scientific Problems ? : Recent Progress and Future Prospects

A. Karpatne, 2017 .

Automated Plantation Mapping in Indonesia Using Remote Sensing Data

Anuj Karpatne, Vipin Kumar, Xiaowei Jia, 2017 .

Intelligent Systems for Geosciences: Accelerating Discovery and Building Community I: Lightning

Anuj Karpatne, Daniel Garijo, Michael J. Friedel, 2017 .

Classifying Heterogeneous Sequential Data by Cyclic Domain Adaptation: An Application in Land Cover Detection

Anuj Karpatne, Xiaowei Jia, Ankush Khandelwal, 2019, SDM.

Tutorial on Machine Learning and Deep Learning for the Environmental and Geosciences

Karthik Kashinath, Prabhat, Anuj Karpatne, 2019 .

Augmenting machine learning algorithms with the addition of a physics based intelligence prior

Anuj Karpatne, Wei-Cheng Lee, Jie Bu, 2020 .

Spatial Context-Aware Networks for Mining Temporal Discriminative Period in Land Cover Detection

Anuj Karpatne, Vipin Kumar, Xiaowei Jia, 2019, SDM.

Building Bridges Between Geoscience and Data Science through Benchmark Data Sets

Mary C. Hill, Anuj Karpatne, Imme Ebert-Uphoff, 2017 .

M ITIGATING P ROPAGATION F AILURES IN PINN S US - ING E VOLUTIONARY S AMPLING

A. Karpatne, P. Perdikaris, Sifan Wang, 2022 .

Deep Learning Enabled Label-free Cell Force Computation in Deformable Fibrous Environments

A. Karpatne, S. Kale, A. Nain, 2022, bioRxiv.

Multi-task Learning for Source Attribution and Field Reconstruction for Methane Monitoring

A. Karpatne, K. Yeo, L. Klein, 2022, 2022 IEEE International Conference on Big Data (Big Data).

Adjoint-Matching Neural Network Surrogates for Fast 4D-Var Data Assimilation

Amit N. Subrahmanya, A. Karpatne, Adrian Sandu, 2021, 2111.08626.

Proximal support tensor machines

A. Karpatne, Reshma Khemchandani, Suresh Chandra, 2012, International Journal of Machine Learning and Cybernetics.

CoPhy-PGNN: Learning Physics-guided Neural Networks with Competing Loss Functions for Solving Eigenvalue Problems

Anuj Karpatne, Wei-Cheng Lee, Jie Bu, 2020, ACM Trans. Intell. Syst. Technol..

Generalized eigenvalue proximal support vector regressor

Anuj Karpatne, Reshma Khemchandani, Suresh Chandra, 2011, Expert Syst. Appl..

Spatio-Temporal Data Mining

Anuj Karpatne, Vipin Kumar, Gowtham Atluri, 2017, ACM Comput. Surv..

Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data

Nagiza F. Samatova, Shashi Shekhar, Anuj Karpatne, 2016, IEEE Transactions on Knowledge and Data Engineering.

Adaptive Heterogeneous Ensemble Learning Using the Context of Test Instances

Anuj Karpatne, Vipin Kumar, A. Karpatne, 2015, 2015 IEEE International Conference on Data Mining.

Predictive Learning in the Presence of Heterogeneity and Limited Training Data

Anuj Karpatne, Vipin Kumar, Ankush Khandelwal, 2014, SDM.

Physics-guided Neural Networks (PGNN): An Application in Lake Temperature Modeling pdf

Anuj Karpatne, Vipin Kumar, Jordan S. Read, 2017, ArXiv.

Physics-Guided Machine Learning for Scientific Discovery: An Application in Simulating Lake Temperature Profiles

X. Jia, J. Willard, A. Karpatne, 2020, Trans. Data Sci..

Physics-Guided Deep Learning for Drag Force Prediction in Dense Fluid-Particulate Systems

Nikhil Muralidhar, Anuj Karpatne, Naren Ramakrishnan, 2020, Big Data.

PhyNet: Physics Guided Neural Networks for Particle Drag Force Prediction in Assembly

Nikhil Muralidhar, Anuj Karpatne, Danesh K. Tafti, 2020, SDM.

Physics-guided Design and Learning of Neural Networks for Predicting Drag Force on Particle Suspensions in Moving Fluids pdf

Nikhil Muralidhar, Anuj Karpatne, Long He, 2019, ArXiv.

Learning Physics-guided Neural Networks with Competing Physics Loss: A Summary of Results in Solving Eigenvalue Problems

Anuj Karpatne, Jie Bu, Mohannad Elhamod, 2021, AAAI Spring Symposium: MLPS.

Learning Neural Networks with Competing Physics Objectives: An Application in Quantum Mechanics pdf

Anuj Karpatne, Wei-Cheng Lee, Jie Bu, 2020, ArXiv.

Monitoring Land-Cover Changes: A Machine-Learning Perspective

Zhe Jiang, Anuj Karpatne, Vipin Kumar, 2016, IEEE Geoscience and Remote Sensing Magazine.

PID-GAN: A GAN Framework based on a Physics-informed Discriminator for Uncertainty Quantification with Physics

Anuj Karpatne, Arka Daw, M. Maruf, 2021, KDD.

Quadratic Residual Networks: A New Class of Neural Networks for Solving Forward and Inverse Problems in Physics Involving PDEs

Anuj Karpatne, Jie Bu, A. Karpatne, 2021, SDM.

ORBIT: Ordering Based Information Transfer Across Space and Time for Global Surface Water Monitoring pdf

Anuj Karpatne, Vipin Kumar, Ankush Khandelwal, 2017, ArXiv.

Building Predictive Models for Noisy and Heterogeneous Data: An Application in Global Monitoring of Inland Water Dynamics

Anuj Karpatne, Vipin Kumar, A. Karpatne, 2015, 2015 IEEE International Conference on Data Mining Workshop (ICDMW).

Earth Science Applications of Sensor Data

Anuj Karpatne, Vipin Kumar, Michael S. Steinbach, 2013, Managing and Mining Sensor Data.

Knowledge-Guided Machine Learning

A. Karpatne, R. Kannan, Vipin Kumar, 2022 .

ReaLSAT, a global dataset of reservoir and lake surface area variations

A. Karpatne, H. Dugan, Paul C. Hanson, 2022, Scientific Data.

Physics-Guided Problem Decomposition for Scaling Deep Learning of High-dimensional Eigen-Solvers: The Case of Schrödinger's Equation

A. Karpatne, Sangeeta Srivastava, Anish Arora, 2022, ArXiv.

Introduction to Data Mining (2nd Edition)

Anuj Karpatne, Pang-Ning Tan, Michael Steinbach, 2018 .

Physics-Guided Architecture (PGA) of Neural Networks for Quantifying Uncertainty in Lake Temperature Modeling pdf

Anuj Karpatne, Jordan S. Read, Alison P. Appling, 2019, SDM.

Discovering Novel Biological Traits From Images Using Phylogeny-Guided Neural Networks

A. Karpatne, T. Berger-Wolf, D. Rubenstein, 2023, KDD.

Incorporating Prior Domain Knowledge into Deep Neural Networks

Nikhil Muralidhar, Mohammad Raihanul Islam, Manish Marwah, 2018, 2018 IEEE International Conference on Big Data (Big Data).

Introduction to Data Mining (Second Edition)

A. Karpatne, M. Steinbach, P. Tan, 2019 .

ReaLSAT: A new Reservoir and Lake Surface Area Timeseries Dataset created using machine learning and satellite imagery

A. Karpatne, H. Dugan, Paul C. Hanson, 2020 .

Physics-Guided AI for Large-Scale Spatiotemporal Data

A. Karpatne, P. Perdikaris, Rose Yu, 2021, KDD.

Physics‐Informed Machine Learning for Optical Modes in Composites

A. Karpatne, V. Podolskiy, Jie Bu, 2021, Advanced Photonics Research.

Discovery of Shifting Patterns in Sequence Classification pdf

Anuj Karpatne, Vipin Kumar, Xiaowei Jia, 2017, ArXiv.

Let There Be Order: Rethinking Ordering in Autoregressive Graph Generation

Kazi Sajeed Mehrab, A. Karpatne, Jie Bu, 2023, ArXiv.

A Graph Convolutional Neural Network Based Approach for Traffic Monitoring Using Augmented Detections with Optical Flow

Anuj Karpatne, Abhijit Sarkar, Ioannis Papakis, 2021, 2021 IEEE International Intelligent Transportation Systems Conference (ITSC).

Quantitative spatio-temporal sequence discovery Group

A. Karpatne, Vijay Borra, 2011 .

Physics Guided Recurrent Neural Networks For Modeling Dynamical Systems: Application to Monitoring Water Temperature And Quality In Lakes pdf

Anuj Karpatne, Vipin Kumar, Michael S. Steinbach, 2018, ArXiv.

Hierarchy‐guided neural network for species classification

A. Karpatne, B. Avants, H. Bart, 2021, Methods in Ecology and Evolution.

Hierarchy-guided Neural Networks for Species Classification

A. Karpatne, B. Avants, H. Bart, 2021, bioRxiv.

A new data mining framework for forest fire mapping

Michael Lau, Vipin Kumar, Anuj Karpatne, 2012, 2012 Conference on Intelligent Data Understanding.

Importance of vegetation type in forest cover estimation

Michael Lau, Anuj Karpatne, Vipin Kumar, 2012, 2012 Conference on Intelligent Data Understanding.

Big Data in Climate: Opportunities and Challenges for Machine Learning

Anuj Karpatne, Vipin Kumar, A. Karpatne, 2017, KDD.

Maximizing Cohesion and Separation in Graph Representation Learning: A Distance-aware Negative Sampling Approach pdf

Anuj Karpatne, M. Maruf, A. Karpatne, 2020, SDM.

Learning Compact Representations of Neural Networks using DiscriminAtive Masking (DAM) pdf

Anuj Karpatne, Jie Bu, Arka Daw, 2021, NeurIPS.

Reduction of Biosensor False Responses and Time Delay Using Dynamic Response and Theory-Guided Machine Learning.

A. Karpatne, Junru Zhang, Purna Srivatsa, 2023, ACS sensors.

Improving biosensor accuracy and speed using dynamic signal change and theory-guided deep learning.

A. Karpatne, Junru Zhang, Purna Srivatsa, 2023, Biosensors & bioelectronics.

PhyFlow: Physics-Guided Deep Learning for Generating Interpretable 3D Flow Fields

A. Karpatne, Naren Ramakrishnan, D. Tafti, 2021, 2021 IEEE International Conference on Data Mining (ICDM).

Modular Compositional Learning Improves 1D Hydrodynamic Lake Model Performance by Merging Process‐Based Modeling With Deep Learning

A. Karpatne, A. Daw, R. Ladwig, 2023, Journal of Advances in Modeling Earth Systems.

Welcome to AI Matters 9(2)

A. Karpatne, Ziyu Yao, 2023, AI Matters.

Tripoles: A New Class of Relationships in Time Series Data

Anuj Karpatne, Vipin Kumar, Snigdhansu Chatterjee, 2017, KDD.

Twin support vector regression for the simultaneous learning of a function and its derivatives

Anuj Karpatne, Reshma Khemchandani, Suresh Chandra, 2012, International Journal of Machine Learning and Cybernetics.

MEMTRACK: A Deep Learning-Based Approach to Microrobot Tracking in Dense and Low-Contrast Environments

Eric J. Leaman, A. Karpatne, B. Behkam, 2023, ArXiv.

A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis

A. Karpatne, Yu Su, David Carlyn, 2023, ArXiv.

Ensemble Learning Methods for Binary Classification with Multi-modality within the Classes

Anuj Karpatne, Vipin Kumar, Ankush Khandelwal, 2015, SDM.

Improving the Accuracy of Physics-Based Hydration-Free Energy Predictions by Machine Learning the Remaining Error Relative to the Experiment.

A. Karpatne, A. Onufriev, I. Tolokh, 2023, Journal of chemical theory and computation.

Knowledge-guided Machine Learning: Current Trends and Future Prospects

X. Jia, A. Karpatne, Vipin Kumar, 2024, ArXiv.

Fish-Vista: A Multi-Purpose Dataset for Understanding & Identification of Traits from Images

Kazi Sajeed Mehrab, A. Karpatne, H. Lapp, 2024, ArXiv.

Mitigating Propagation Failures in Physics-informed Neural Networks using Retain-Resample-Release (R3) Sampling

A. Karpatne, P. Perdikaris, Sifan Wang, 2022, ICML.