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ORCIDDan Lu 0001
Person information
- affiliation: Oak Ridge National Laboratory, Department of Computer Science and Mathmatics, TN, USA
- affiliation (PhD 2012): Florida State University, Tallahassee, FL, USA
Other persons with the same name
- Dan Lu — disambiguation page
- Dan Lu 0002 — Digital Art, Indianapolis, IN, USA (and 1 more)
- Dan Lu 0003 — Xi'an Jiaotong University, Smiles Laboratory, China
- Dan Lu 0004
![[0000-0001-6410-8422]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-6410-8422")
— Harbin Engineering University, College of Computer Science and Technology, China - Dan Lu 0005 — Civil Aviation University of China, Tianjin, China
- Dan Lu 0006 — Shandong University, School of Control Science and Engineering, Jinan, China
- Dan Lu 0007 — State Grid Henan Economic Research Institute, Zhengzhou, China (and 1 more)
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Journal Articles
- 2023
[j3]Ming Fan, Siyan Liu, Dan Lu, Sudershan Gangrade, Shih-Chieh Kao:
Explainable machine learning model for multi-step forecasting of reservoir inflow with uncertainty quantification. Environ. Model. Softw. 170: 105849 (2023)- 2019
- [j2]Shaoxing Mo, Xiaoqing Shi, Dan Lu, Ming Ye, Jichun Wu:
An adaptive Kriging surrogate method for efficient uncertainty quantification with an application to geological carbon sequestration modeling. Comput. Geosci. 125: 69-77 (2019) - 2014
- [j1]Dan Lu, Ming Ye, Mary C. Hill, Eileen P. Poeter, Gary P. Curtis:
A computer program for uncertainty analysis integrating regression and Bayesian methods. Environ. Model. Softw. 60: 45-56 (2014)
Conference and Workshop Papers
- 2022
- [c8]Hoang Tran, Dan Lu, Guannan Zhang:
Exploiting the Local Parabolic Landscapes of Adversarial Losses to Accelerate Black-Box Adversarial Attack. ECCV (5) 2022: 317-334 - [c7]Ming Fan, Lujun Zhang, Siyan Liu, Tiantian Yang, Dan Lu:
Identifying Hydrometeorological Factors Influencing Reservoir Releases Using Machine Learning Methods. ICDM (Workshops) 2022: 1102-1110 - [c6]Siyan Liu, Dan Lu, Daniel M. Ricciuto, Anthony P. Walker:
Improving net ecosystem CO2 flux prediction using memory-based interpretable machine learning. ICDM (Workshops) 2022: 1111-1119 - [c5]Siyan Liu, Pei Zhang, Dan Lu, Guannan Zhang:
PI3NN: Out-of-distribution-aware Prediction Intervals from Three Neural Networks. ICLR 2022 - 2021
- [c4]Jiaxin Zhang, Hoang Tran, Dan Lu, Guannan Zhang:
Enabling long-range exploration in minimization of multimodal functions. UAI 2021: 1639-1649 - 2020
- [c3]Dan Lu, Daniel M. Ricciuto:
Efficient Distance-based Global Sensitivity Analysis for Terrestrial Ecosystem Modeling. ICDM (Workshops) 2020: 324-332 - 2019
- [c2]Dan Lu, Siyan Liu, Daniel M. Ricciuto:
An Efficient Bayesian Method for Advancing the Application of Deep Learning in Earth Science. ICDM Workshops 2019: 270-278 - [c1]Dan Lu, Daniel M. Ricciuto:
Learning-Based Inversion-Free Model-Data Integration to Advance Ecosystem Model Prediction. ICDM Workshops 2019: 279-287
Informal and Other Publications
- 2024
- [i8]Minglei Yang, Pengjun Wang, Ming Fan, Dan Lu, Yanzhao Cao, Guannan Zhang:
Conditional Pseudo-Reversible Normalizing Flow for Surrogate Modeling in Quantifying Uncertainty Propagation. CoRR abs/2404.00502 (2024) - [i7]Xiao Wang, Aristeidis Tsaris, Siyan Liu, Jong-Youl Choi, Ming Fan, Wei Zhang, Junqi Yin, Moetasim Ashfaq, Dan Lu, Prasanna Balaprakash:
ORBIT: Oak Ridge Base Foundation Model for Earth System Predictability. CoRR abs/2404.14712 (2024) - [i6]Aristeidis Tsaris, Chengming Zhang, Xiao Wang, Junqi Yin, Siyan Liu, Moetasim Ashfaq, Ming Fan, Jong-Youl Choi, Mohamed Wahib, Dan Lu, Prasanna Balaprakash, Fei-Yue Wang:
Sequence Length Scaling in Vision Transformers for Scientific Images on Frontier. CoRR abs/2405.15780 (2024) - [i5]Junqi Yin, Siming Liang, Siyan Liu, Feng Bao, Hristo G. Chipilski, Dan Lu, Guannan Zhang:
A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics. CoRR abs/2407.12168 (2024) - 2023
- [i4]Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Shiyang Chen, Chengming Zhang, Masahiro Tanaka, Xiaoxia Wu, Jeff Rasley, Ammar Ahmad Awan, Connor Holmes, Martin Cai, Adam Ghanem, Zhongzhu Zhou, Yuxiong He, Pete Luferenko, Divya Kumar, Jonathan A. Weyn, Ruixiong Zhang, Sylwester Klocek, Volodymyr Vragov, Mohammed AlQuraishi, Gustaf Ahdritz, Christina Floristean, Cristina Negri, Rao Kotamarthi, Venkatram Vishwanath, Arvind Ramanathan, Sam Foreman, Kyle Hippe, Troy Arcomano, Romit Maulik, Maxim Zvyagin, Alexander Brace, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Zhen Xie, Diangen Lin, Maulik Shukla, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Prasanna Balaprakash, Gina Tourassi, John Gounley, Heidi A. Hanson, Thomas E. Potok, Massimiliano Lupo Pasini, Kate Evans, Dan Lu, Dalton D. Lunga, Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar, Isaac Lyngaas, Xiao Wang, Guojing Cong, Pei Zhang, Ming Fan, Siyan Liu, Adolfy Hoisie, Shinjae Yoo, Yihui Ren, William Tang, Kyle Felker, Alexey Svyatkovskiy, Hang Liu, Ashwin M. Aji, Angela Dalton, Michael J. Schulte, Karl Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens:
DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. CoRR abs/2310.04610 (2023) - 2021
- [i3]Siyan Liu, Pei Zhang, Dan Lu, Guannan Zhang:
PI3NN: Prediction intervals from three independently trained neural networks. CoRR abs/2108.02327 (2021) - 2020
- [i2]Jiaxin Zhang, Hoang Tran, Dan Lu, Guannan Zhang:
A Scalable Evolution Strategy with Directional Gaussian Smoothing for Blackbox Optimization. CoRR abs/2002.03001 (2020) - 2019
- [i1]Dan Lu, Daniel M. Ricciuto:
Efficient surrogate modeling methods for large-scale Earth system models based on machine learning techniques. CoRR abs/1901.05125 (2019)
Coauthor Index
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