Anuj Karpatne
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
29
Venues
11
Active years
2014–2026
Best venue rank
A*
Where they publish
Papers
29 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | AAAI | Knowledge-Guided Machine Learning: A Paradigm Shift in AI for Science. | Anuj Karpatne, Xiaowei Jia, Vipin Kumar |
| 2025 | CVPR | Prompt-CAM: Making Vision Transformers Interpretable for Fine-Grained Analysis. | Arpita Chowdhury, Dipanjyoti Paul, Zheda Mai, Jianyang Gu, Ziheng Zhang, Kazi Sajeed Mehrab, Elizabeth G. Campolongo, Daniel I. Rubenstein, Charles V. Stewart, Anuj Karpatne, Tanya Y. Berger-Wolf, Yu Su, Wei-Lun Chao |
| 2025 | CVPR | Fish-Vista: A Multi-Purpose Dataset for Understanding & Identification of Traits from Images. | Kazi Sajeed Mehrab, M. Maruf, Arka Daw, Abhilash Neog, Harish Babu Manogaran, Mridul Khurana, Zhenyang Feng, Bahadir Altintas, Yasin Bakis, Elizabeth G. Campolongo, Matthew J. Thompson, Xiaojun Wang, Hilmar Lapp, Tanya Y. Berger-Wolf, Paula M. Mabee, Henry L. Bart Jr., Wei-Lun Chao, Wasila M. Dahdul, Anuj Karpatne |
| 2025 | ICCV | Taxadiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation. | Amin Karimi Monsefi, Mridul Khurana, Rajiv Ramnath, Anuj Karpatne, Wei-Lun Chao, Cheng Zhang |
| 2025 | ICLR | A Unified Framework for Forward and Inverse Problems in Subsurface Imaging using Latent Space Translations. | Naveen Gupta, Medha Sawhney, Arka Daw, Youzuo Lin, Anuj Karpatne |
| 2025 | ICLR | What Do You See in Common? Learning Hierarchical Prototypes over Tree-of-Life to Discover Evolutionary Traits. | Harish Babu Manogaran, M. Maruf, Arka Daw, Kazi Sajeed Mehrab, Caleb Patrick Charpentier, Josef C. Uyeda, Wasila M. Dahdul, Matthew J. Thompson, Elizabeth G. Campolongo, Kaiya L. Provost, Wei-Lun Chao, Tanya Y. Berger-Wolf, Paula M. Mabee, Hilmar Lapp, Anuj Karpatne |
| 2024 | ECCV | Hierarchical Conditioning of Diffusion Models Using Tree-of-Life for Studying Species Evolution. | Mridul Khurana, Arka Daw, M. Maruf, Josef C. Uyeda, Wasila M. Dahdul, Caleb Charpentier, Yasin Bakis, Henry L. Bart Jr., Paula M. Mabee, Hilmar Lapp, James P. Balhoff, Wei-Lun Chao, Charles V. Stewart, Tanya Y. Berger-Wolf, Anuj Karpatne |
| 2024 | ICLR | A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis. | 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 |
| 2024 | ICML | Neuro-Visualizer: A Novel Auto-Encoder-Based Loss Landscape Visualization Method With an Application in Knowledge-Guided Machine Learning. | Mohannad Elhamod, Anuj Karpatne |
| 2023 | ICML | Mitigating Propagation Failures in Physics-informed Neural Networks using Retain-Resample-Release (R3) Sampling. | Arka Daw, Jie Bu, Sifan Wang, Paris Perdikaris, Anuj Karpatne |
| 2023 | KDD | Discovering Novel Biological Traits From Images Using Phylogeny-Guided Neural Networks. | 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 |
| 2021 | ICDM | PhyFlow: Physics-Guided Deep Learning for Generating Interpretable 3D Flow Fields. | Nikhil Muralidhar, Jie Bu, Ze Cao, Neil Raj, Naren Ramakrishnan, Danesh K. Tafti, Anuj Karpatne |
| 2021 | KDD | PID-GAN: A GAN Framework based on a Physics-informed Discriminator for Uncertainty Quantification with Physics. | Arka Daw, M. Maruf, Anuj Karpatne |
| 2021 | KDD | Physics-Guided AI for Large-Scale Spatiotemporal Data. | Rose Yu, Paris Perdikaris, Anuj Karpatne |
| 2021 | SDM | Quadratic Residual Networks: A New Class of Neural Networks for Solving Forward and Inverse Problems in Physics Involving PDEs. | Jie Bu, Anuj Karpatne |
| 2021 | SDM | Maximizing Cohesion and Separation in Graph Representation Learning: A Distance-aware Negative Sampling Approach. | M. Maruf, Anuj Karpatne |
| 2020 | IGARSS | Process Guided Deep Learning for Modeling Physical Systems: An Application in Lake Temperature Modeling. | Xiaowei Jia, Jared Willard, Anuj Karpatne, Jordan S. Read, Jacob A. Zwart, Michael S. Steinbach, Vipin Kumar |
| 2020 | SDM | Physics-Guided Architecture (PGA) of Neural Networks for Quantifying Uncertainty in Lake Temperature Modeling. | Arka Daw, R. Quinn Thomas, Cayelan C. Carey, Jordan S. Read, Alison P. Appling, Anuj Karpatne |
| 2020 | SDM | PhyNet: Physics Guided Neural Networks for Particle Drag Force Prediction in Assembly. | Nikhil Muralidhar, Jie Bu, Ze Cao, Long He, Naren Ramakrishnan, Danesh K. Tafti, Anuj Karpatne |
| 2019 | IJCAI | Recurrent Generative Networks for Multi-Resolution Satellite Data: An Application in Cropland Monitoring. | Xiaowei Jia, Mengdie Wang, Ankush Khandelwal, Anuj Karpatne, Vipin Kumar |
| 2019 | SDM | Spatial Context-Aware Networks for Mining Temporal Discriminative Period in Land Cover Detection. | Xiaowei Jia, Sheng Li, Ankush Khandelwal, Guruprasad Nayak, Anuj Karpatne, Vipin Kumar |
| 2019 | SDM | Classifying Heterogeneous Sequential Data by Cyclic Domain Adaptation: An Application in Land Cover Detection. | Xiaowei Jia, Guruprasad Nayak, Ankush Khandelwal, Anuj Karpatne, Vipin Kumar |
| 2019 | SDM | Physics Guided RNNs for Modeling Dynamical Systems: A Case Study in Simulating Lake Temperature Profiles. | Xiaowei Jia, Jared Willard, Anuj Karpatne, Jordan S. Read, Jacob Zwart, Michael S. Steinbach, Vipin Kumar |
| 2017 | KDD | Tripoles: A New Class of Relationships in Time Series Data. | Saurabh Agrawal, Gowtham Atluri, Anuj Karpatne, William Haltom, Stefan Liess, Snigdhansu Chatterjee, Vipin Kumar |
| 2017 | KDD | Big Data in Climate: Opportunities and Challenges for Machine Learning. | Anuj Karpatne, Vipin Kumar |
| 2015 | ICDM | Adaptive Heterogeneous Ensemble Learning Using the Context of Test Instances. | Anuj Karpatne, Vipin Kumar |
| 2015 | ICDM | Building Predictive Models for Noisy and Heterogeneous Data: An Application in Global Monitoring of Inland Water Dynamics. | Anuj Karpatne, Vipin Kumar |
| 2015 | SDM | Ensemble Learning Methods for Binary Classification with Multi-modality within the Classes. | Anuj Karpatne, Ankush Khandelwal, Vipin Kumar |
| 2014 | SDM | Predictive Learning in the Presence of Heterogeneity and Limited Training Data. | Anuj Karpatne, Ankush Khandelwal, Shyam Boriah, Vipin Kumar |