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Books and Theses
- 2023
[b1]Simiao Ren:
Deep Learning for the modeling and design of artificial electromagnetic materials. Duke University, Durham, NC, USA, 2023
Journal Articles
- 2022
- [j2]Simiao Ren
, Jordan M. Malof, Rob Fetter, Robert H. Beach, James Rineer, Kyle Bradbury:
Utilizing Geospatial Data for Assessing Energy Security: Mapping Small Solar Home Systems Using Unmanned Aerial Vehicles and Deep Learning. ISPRS Int. J. Geo Inf. 11(4): 222 (2022) - [j1]Zachary D. Calhoun, Saad Lahrichi, Simiao Ren, Jordan M. Malof, Kyle Bradbury:
Self-Supervised Encoders Are Better Transfer Learners in Remote Sensing Applications. Remote. Sens. 14(21): 5500 (2022)
Conference and Workshop Papers
- 2024
- [c6]Simiao Ren, Francesco Luzi, Saad Lahrichi, Kaleb Kassaw, Leslie M. Collins, Kyle Bradbury, Jordan M. Malof:
Segment anything, from space? WACV 2024: 8340-8350 - 2023
- [c5]Gregory P. Spell, Simiao Ren, Leslie M. Collins, Jordan M. Malof:
Mixture Manifold Networks: A Computationally Efficient Baseline for Inverse Modeling. AAAI 2023: 9874-9881 - [c4]En Wei, Simiao Ren:
Drowning Detection based on YOLOv8 improved by GP-GAN Augmentation. Tiny Papers @ ICLR 2023 - 2022
- [c3]Juncheng Dong, Simiao Ren, Yang Deng, Omar Khatib, Jordan M. Malof, Mohammadreza Soltani, Willie Padilla, Vahid Tarokh:
Blaschke Product Neural Networks (BPNN): A Physics-Infused Neural Network for Phase Retrieval of Meromorphic Functions. ICLR 2022 - 2021
- [c2]Yang Deng, Juncheng Dong, Simiao Ren, Omar Khatib, Mohammadreza Soltani, Vahid Tarokh, Willie Padilla, Jordan M. Malof:
Benchmarking Data-driven Surrogate Simulators for Artificial Electromagnetic Materials. NeurIPS Datasets and Benchmarks 2021 - 2020
- [c1]Simiao Ren, Willie Padilla, Jordan M. Malof:
Benchmarking Deep Inverse Models over time, and the Neural-Adjoint method. NeurIPS 2020
Informal and Other Publications
- 2023
- [i8]Simiao Ren, Yang Deng, Willie J. Padilla, Leslie M. Collins, Jordan M. Malof:
Deep Active Learning for Scientific Computing in the Wild. CoRR abs/2302.00098 (2023) - [i7]Simiao Ren, Francesco Luzi, Saad Lahrichi, Kaleb Kassaw, Leslie M. Collins, Kyle Bradbury, Jordan M. Malof:
Segment anything, from space? CoRR abs/2304.13000 (2023) - 2022
- [i6]Simiao Ren, Yang Deng, Willie J. Padilla, Jordan M. Malof:
Hyperparameter-free deep active learning for regression problems via query synthesis. CoRR abs/2201.12632 (2022) - [i5]Simiao Ren, Wei Hu, Kyle Bradbury, Dylan Harrison-Atlas, Laura Malaguzzi Valeri, Brian Murray, Jordan M. Malof:
Automated Extraction of Energy Systems Information from Remotely Sensed Data: A Review and Analysis. CoRR abs/2202.12939 (2022) - [i4]Gregory P. Spell, Simiao Ren, Leslie M. Collins, Jordan M. Malof:
Mixture Manifold Networks: A Computationally Efficient Baseline for Inverse Modeling. CoRR abs/2211.14366 (2022) - 2021
- [i3]Juncheng Dong, Simiao Ren, Yang Deng, Omar Khatib, Jordan M. Malof, Mohammadreza Soltani, Willie Padilla, Vahid Tarokh:
Blaschke Product Neural Networks (BPNN): A Physics-Infused Neural Network for Phase Retrieval of Meromorphic Functions. CoRR abs/2111.13311 (2021) - [i2]Simiao Ren, Ashwin Mahendra, Omar Khatib, Yang Deng, Willie J. Padilla, Jordan M. Malof:
Inverse deep learning methods and benchmarks for artificial electromagnetic material design. CoRR abs/2112.10254 (2021) - 2020
- [i1]Simiao Ren, Willie Padilla, Jordan M. Malof:
Benchmarking deep inverse models over time, and the neural-adjoint method. CoRR abs/2009.12919 (2020)
Coauthor Index
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