Anuj Karpatne
Orcid: 0000-0003-1647-3534
According to our database1,
Anuj Karpatne
authored at least 81 papers
between 2011 and 2024.
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Bibliography
2024
2023
A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis.
CoRR, 2023
MEMTRACK: A Deep Learning-Based Approach to Microrobot Tracking in Dense and Low-Contrast Environments.
CoRR, 2023
CoRR, 2023
Beyond Discriminative Regions: Saliency Maps as Alternatives to CAMs for Weakly Supervised Semantic Segmentation.
CoRR, 2023
CoRR, 2023
Discovering Novel Biological Traits From Images Using Phylogeny-Guided Neural Networks.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
Mitigating Propagation Failures in Physics-informed Neural Networks using Retain-Resample-Release (R3) Sampling.
Proceedings of the International Conference on Machine Learning, 2023
2022
<i>CoPhy</i>-PGNN: Learning Physics-guided Neural Networks with Competing Loss Functions for Solving Eigenvalue Problems.
ACM Trans. Intell. Syst. Technol., 2022
CoRR, 2022
Physics-Guided Problem Decomposition for Scaling Deep Learning of High-dimensional Eigen-Solvers: The Case of Schrödinger's Equation.
CoRR, 2022
Multi-task Learning for Source Attribution and Field Reconstruction for Methane Monitoring.
Proceedings of the IEEE International Conference on Big Data, 2022
2021
Physics-Guided Machine Learning for Scientific Discovery: An Application in Simulating Lake Temperature Profiles.
Trans. Data Sci., 2021
CoRR, 2021
A Data-Driven Approach to Full-Field Damage and Failure Pattern Prediction in Microstructure-Dependent Composites using Deep Learning.
CoRR, 2021
Maximizing Cohesion and Separation in Graph Representation Learning: A Distance-aware Negative Sampling Approach.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021
Quadratic Residual Networks: A New Class of Neural Networks for Solving Forward and Inverse Problems in Physics Involving PDEs.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021
Learning Compact Representations of Neural Networks using DiscriminAtive Masking (DAM).
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021
PID-GAN: A GAN Framework based on a Physics-informed Discriminator for Uncertainty Quantification with Physics.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021
A Graph Convolutional Neural Network Based Approach for Traffic Monitoring Using Augmented Detections with Optical Flow.
Proceedings of the 24th IEEE International Intelligent Transportation Systems Conference, 2021
Proceedings of the IEEE International Conference on Data Mining, 2021
Learning Physics-guided Neural Networks with Competing Physics Loss: A Summary of Results in Solving Eigenvalue Problems.
Proceedings of the AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 22nd - to, 2021
2020
GCNNMatch: Graph Convolutional Neural Networks for Multi-Object Tracking via Sinkhorn Normalization.
CoRR, 2020
Learning Neural Networks with Competing Physics Objectives: An Application in Quantum Mechanics.
CoRR, 2020
Physics-Guided Deep Learning for Drag Force Prediction in Dense Fluid-Particulate Systems.
Big Data, 2020
PhyNet: Physics Guided Neural Networks for Particle Drag Force Prediction in Assembly.
Proceedings of the 2020 SIAM International Conference on Data Mining, 2020
Physics-Guided Architecture (PGA) of Neural Networks for Quantifying Uncertainty in Lake Temperature Modeling.
Proceedings of the 2020 SIAM International Conference on Data Mining, 2020
Biodiversity Image Quality Metadata Augments Convolutional Neural Network Classification of Fish Species.
Proceedings of the Metadata and Semantic Research - 14th International Conference, 2020
Process Guided Deep Learning for Modeling Physical Systems: An Application in Lake Temperature Modeling.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020
2019
IEEE Trans. Knowl. Data Eng., 2019
Physics-guided Design and Learning of Neural Networks for Predicting Drag Force on Particle Suspensions in Moving Fluids.
CoRR, 2019
A Fast-Optimal Guaranteed Algorithm For Learning Sub-Interval Relationships in Time Series.
CoRR, 2019
Physics Guided RNNs for Modeling Dynamical Systems: A Case Study in Simulating Lake Temperature Profiles.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019
Classifying Heterogeneous Sequential Data by Cyclic Domain Adaptation: An Application in Land Cover Detection.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019
Spatial Context-Aware Networks for Mining Temporal Discriminative Period in Land Cover Detection.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019
Recurrent Generative Networks for Multi-Resolution Satellite Data: An Application in Cropland Monitoring.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
2018
ACM Comput. Surv., 2018
Physics Guided Recurrent Neural Networks For Modeling Dynamical Systems: Application to Monitoring Water Temperature And Quality In Lakes.
CoRR, 2018
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018
2017
IEEE Trans. Knowl. Data Eng., 2017
ORBIT: Ordering Based Information Transfer Across Space and Time for Global Surface Water Monitoring.
CoRR, 2017
CoRR, 2017
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017
Joint sparse auto-encoder: A semi-supervised spatio-temporal approach in mapping large-scale croplands.
Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017
2016
Global Monitoring of Inland Water Dynamics: State-of-the-Art, Challenges, and Opportunities.
Proceedings of the Computational Sustainability, 2016
Identifying dynamic changes with noisy labels in spatial-temporal data: A study on large-scale water monitoring application.
Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016
2015
Comput. Sci. Eng., 2015
Ensemble Learning Methods for Binary Classification with Multi-modality within the Classes.
Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015
Building Predictive Models for Noisy and Heterogeneous Data: An Application in Global Monitoring of Inland Water Dynamics.
Proceedings of the IEEE International Conference on Data Mining Workshop, 2015
Proceedings of the 2015 IEEE International Conference on Data Mining, 2015
2014
Proceedings of the 2014 SIAM International Conference on Data Mining, 2014
2013
Twin support vector regression for the simultaneous learning of a function and its derivatives.
Int. J. Mach. Learn. Cybern., 2013
Proceedings of the Managing and Mining Sensor Data, 2013
2012
Proceedings of the 2012 Conference on Intelligent Data Understanding, 2012
Proceedings of the 2012 Conference on Intelligent Data Understanding, 2012
2011