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Arka Daw
Arka Daw
PhD Student in Computer Science, Virginia Tech
Verified email at vt.edu
Title
Cited by
Cited by
Year
Physics-guided neural networks (pgnn): An application in lake temperature modeling
A Daw, A Karpatne, WD Watkins, JS Read, V Kumar
Knowledge Guided Machine Learning, 353-372, 2022
2202022
Physics-guided architecture (pga) of neural networks for quantifying uncertainty in lake temperature modeling
A Daw, RQ Thomas, CC Carey, JS Read, AP Appling, A Karpatne
Proceedings of the 2020 siam international conference on data mining, 532-540, 2020
1392020
Rethinking the Importance of Sampling in Physics-informed Neural Networks
A Daw, J Bu, S Wang, P Perdikaris, A Karpatne
arXiv preprint arXiv:2207.02338, 2022
572022
PID-GAN: A GAN Framework based on a Physics-informed Discriminator for Uncertainty Quantification with Physics
A Daw, M Maruf, A Karpatne
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021
342021
Mitigating propagation failures in physics-informed neural networks using retain-resample-release (r3) sampling
A Daw, J Bu, S Wang, P Perdikaris, A Karpatne
arXiv preprint arXiv:2207.02338, 2022
152022
Mitigating propagation failures in pinns using evolutionary sampling
A Daw, J Bu, S Wang, P Perdikaris, A Karpatne
142022
Physics-guided neural networks (pgnn): An application in lake temperature modeling, arXiv
A Daw, A Karpatne, W Watkins, J Read, V Kumar
arXiv preprint arXiv:1710.11431, 2017
112017
Learning compact representations of neural networks using discriminative masking (DAM)
J Bu, A Daw, M Maruf, A Karpatne
Advances in Neural Information Processing Systems 34, 3491-3503, 2021
42021
Physics-aware Architecture of Neural Networks for Uncertainty Quantification: Application in Lake Temperature Modeling
A Daw, A Karpatne
FEED Workshop at Knowledge Discovery and Data Mining Conference (SIGKDD …, 2019
42019
Multi-task Learning for Source Attribution and Field Reconstruction for Methane Monitoring
A Daw, K Yeo, A Karpatne, L Klein
2022 IEEE International Conference on Big Data (Big Data), 4835-4841, 2022
32022
Modular Compositional Learning Improves 1D Hydrodynamic Lake Model Performance by Merging Process‐Based Modeling With Deep Learning
R Ladwig, A Daw, EA Albright, C Buelo, A Karpatne, MF Meyer, A Neog, ...
Journal of Advances in Modeling Earth Systems 16 (1), e2023MS003953, 2024
12024
Physics-guided architecture (PGA) of LSTM models for uncertainty quantification in lake temperature modeling
A Daw, RQ Thomas, CC Carey, JS Read, AP Appling, A Karpatne
Knowledge Guided Machine Learning, 399-416, 2022
12022
Physics-Informed Discriminator (PID) for Conditional Generative Adversarial Nets
A Daw, M Maruf, A Karpatne
Advances in Neural Information Processing Systems, Machine Learning and …, 2020
12020
Physics-informed Machine Learning with Uncertainty Quantification
A Daw
Virginia Tech, 2024
2024
Motion Enhanced Multi‐Level Tracker (MEMTrack): A Deep Learning‐Based Approach to Microrobot Tracking in Dense and Low‐Contrast Environments
M Sawhney, B Karmarkar, EJ Leaman, A Daw, A Karpatne, B Behkam
Advanced Intelligent Systems, 2300590, 2024
2024
MEMTRACK: A Deep Learning-Based Approach to Microrobot Tracking in Dense and Low-Contrast Environments
M Sawhney, B Karmarkar, EJ Leaman, A Daw, A Karpatne, B Behkam
arXiv preprint arXiv:2310.09441, 2023
2023
Beyond Discriminative Regions: Saliency Maps as Alternatives to CAMs for Weakly Supervised Semantic Segmentation
M Maruf, A Daw, A Dutta, J Bu, A Karpatne
arXiv preprint arXiv:2308.11052, 2023
2023
Source Identification and Field Reconstruction of Advection-Diffusion Process from Sparse Sensor Measurements
A Daw, K Yeo, A Karpatne, L Klein
Advances in Neural Information Processing Systems, Machine Learning and …, 2022
2022
Deep Learning Enabled Label-free Cell Force Computation in Deformable Fibrous Environments
A Padhi, A Daw, M Sawhney, MM Talukder, A Agashe, S Kale, A Karpatne, ...
https://www.biorxiv.org/content/10.1101/2022.10.24.513423v1, 2022
2022
Beyond Observed Connections: Link Injection
J Bu, M Maruf, A Daw
arXiv preprint arXiv:2009.04447, 2020
2020
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