Dan Lu - RankMe

38 papers A* 1A 4C 1Journal 24Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AGFormer: Adaptive Spatiotemporal graph informed transformer for multi-reservoir inflow forecasting. Environ. Model. Softw. Ming Fan, Pengfei Hu, Xiaoxue Han, Wei Zhang, Hyun Kang, Yue Ning, Dan Lu
2025	—	`conf`	Adaptive Graph Learning with Transformer for Multi-Reservoir Inflow Prediction. ICDM (Workshops) Pengfei Hu, Ming Fan, Xiaoxue Han, Chang Lu, Wei Zhang, Hyun Kang, Yue Ning, Dan Lu
2025	J	`jnl`	Adaptive Graph Learning with Transformer for Multi-Reservoir Inflow Prediction. CoRR Pengfei Hu, Ming Fan, Xiaoxue Han, Chang Lu, Wei Zhang, Hyun Kang, Yue Ning, Dan Lu
2025	J	`jnl`	Decoding Memories: An Efficient Pipeline for Self-Consistency Hallucination Detection. CoRR Weizhi Gao, Xiaorui Liu, Feiyi Wang, Dan Lu, Junqi Yin
2025	J	`jnl`	Diffusion-based supervised learning of generative models for efficient sampling of multimodal distributions. CoRR Hoang Tran, Zezhong Zhang, Feng Bao, Dan Lu, Guannan Zhang
2025	A	`conf`	Distributed Cross-Channel Hierarchical Aggregation for Foundation Models. SC Aristeidis Tsaris, Isaac Lyngaas, John H. Lagergren, Mohamed Wahib, Larry M. York, Prasanna Balaprakash, Dan Lu, Feiyi Wang, Xiao Wang
2025	J	`jnl`	Distributed Cross-Channel Hierarchical Aggregation for Foundation Models. CoRR Aristeidis Tsaris, Isaac Lyngaas, John H. Lagergren, Mohamed Wahib, Larry M. York, Prasanna Balaprakash, Dan Lu, Yi-Fei Wang, Xiao Wang
2025	J	`jnl`	GenAI4UQ: A software for forward and inverse uncertainty quantification using conditional generative AI. SoftwareX Ming Fan, Zezhong Zhang, Dan Lu, Guannan Zhang
2025	J	`jnl`	HydroDCM: Hydrological Domain-Conditioned Modulation for Cross-Reservoir Inflow Prediction. CoRR Pengfei Hu, Ming Fan, Xiaoxue Han, Chang Lu, Yue Ning, Dan Lu
2025	A	`conf`	ORBIT-2: Scaling Exascale Vision Foundation Models for Weather and Climate Downscaling. SC Xiao Wang, Jong-Youl Choi, Takuya Kurihana, Isaac Lyngaas, Hong-Jun Yoon, Xi Xiao, David Pugmire, Ming Fan, Nasik Muhammad Nafi, Aristeidis Tsaris, Ashwin M. Aji, Maliha Hossain, Mohamed Wahib, Dali Wang, Peter E. Thornton, Prasanna Balaprakash, Moetasim Ashfaq, Dan Lu
2025	J	`jnl`	ORBIT-2: Scaling Exascale Vision Foundation Models for Weather and Climate Downscaling. CoRR Xiao Wang, Jong-Youl Choi, Takuya Kurihana, Isaac Lyngaas, Hong-Jun Yoon, Ming Fan, Nasik Muhammad Nafi, Aristeidis Tsaris, Ashwin M. Aji, Maliha Hossain, Mohamed Wahib, Dali Wang, Peter E. Thornton, Prasanna Balaprakash, Moetasim Ashfaq, Dan Lu
2024	—	`conf`	A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics. SC Workshops Junqi Yin, Siming Liang, Siyan Liu, Feng Bao, Hristo G. Chipilski, Dan Lu, Guannan Zhang
2024	J	`jnl`	A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics. CoRR Junqi Yin, Siming Liang, Siyan Liu, Feng Bao, Hristo G. Chipilski, Dan Lu, Guannan Zhang
2024	J	`jnl`	Conditional Pseudo-Reversible Normalizing Flow for Surrogate Modeling in Quantifying Uncertainty Propagation. CoRR Minglei Yang, Pengjun Wang, Ming Fan, Dan Lu, Yanzhao Cao, Guannan Zhang
2024	J	`jnl`	Distance preserving machine learning for uncertainty aware accelerator capacitance predictions. Mach. Learn. Sci. Technol. Steven Goldenberg, Malachi Schram, Kishansingh Rajput, Thomas Britton, Chris Pappas, Dan Lu, Jared Walden, Majdi I. Radaideh, Sarah Cousineau, Sudarshan Harave
2024	J	`jnl`	GenAI4UQ: A Software for Inverse Uncertainty Quantification Using Conditional Generative Models. CoRR Ming Fan, Zezhong Zhang, Dan Lu, Guannan Zhang
2024	A	`conf`	ORBIT: Oak Ridge Base Foundation Model for Earth System Predictability. SC Xiao Wang, Siyan Liu, Aristeidis Tsaris, Jong-Youl Choi, Ashwin M. Aji, Ming Fan, Wei Zhang, Junqi Yin, Moetasim Ashfaq, Dan Lu, Prasanna Balaprakash
2024	J	`jnl`	ORBIT: Oak Ridge Base Foundation Model for Earth System Predictability. CoRR Xiao Wang, Aristeidis Tsaris, Siyan Liu, Jong-Youl Choi, Ming Fan, Wei Zhang, Junqi Yin, Moetasim Ashfaq, Dan Lu, Prasanna Balaprakash
2024	J	`jnl`	Sequence Length Scaling in Vision Transformers for Scientific Images on Frontier. CoRR 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
2023	C	`conf`	Accelerating Scientific Simulations with Bi-Fidelity Weighted Transfer Learning. ICMLA Katarzyna Borowiec, Dan Lu, Vikas Chandan, Samrat Chatterjee, Pradeep Ramuhalli, Ramakrishna Tipireddy, Mahantesh Halappanavar, Frank Liu
2023	J	`jnl`	DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. CoRR 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 W. Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens
2023	J	`jnl`	Distance Preserving Machine Learning for Uncertainty Aware Accelerator Capacitance Predictions. CoRR Steven Goldenberg, Malachi Schram, Kishansingh Rajput, Thomas Britton, Chris Pappas, Dan Lu, Jared Walden, Majdi I. Radaideh, Sarah Cousineau, Sudarshan Harave
2023	J	`jnl`	Explainable machine learning model for multi-step forecasting of reservoir inflow with uncertainty quantification. Environ. Model. Softw. Ming Fan, Siyan Liu, Dan Lu, Sudershan Gangrade, Shih-Chieh Kao
2023	J	`jnl`	Multi-module based CVAE to predict HVCM faults in the SNS accelerator. CoRR Yasir Alanazi, Malachi Schram, Kishansingh Rajput, Steven Goldenberg, Lasitha Vidyaratne, Chris Pappas, Majdi I. Radaideh, Dan Lu, Pradeep Ramuhalli, Sarah Cousineau
2022	—	`conf`	Exploiting the Local Parabolic Landscapes of Adversarial Losses to Accelerate Black-Box Adversarial Attack. ECCV (5) Hoang Tran, Dan Lu, Guannan Zhang
2022	—	`conf`	Identifying Hydrometeorological Factors Influencing Reservoir Releases Using Machine Learning Methods. ICDM (Workshops) Ming Fan, Lujun Zhang, Siyan Liu, Tiantian Yang, Dan Lu
2022	—	`conf`	Improving net ecosystem CO2 flux prediction using memory-based interpretable machine learning. ICDM (Workshops) Siyan Liu, Dan Lu, Daniel M. Ricciuto, Anthony P. Walker
2022	A*	`conf`	PI3NN: Out-of-distribution-aware Prediction Intervals from Three Neural Networks. ICLR Siyan Liu, Pei Zhang, Dan Lu, Guannan Zhang
2022	J	`jnl`	Time series anomaly detection in power electronics signals with recurrent and ConvLSTM autoencoders. Digit. Signal Process. Majdi I. Radaideh, Chris Pappas, Jared Walden, Dan Lu, Lasitha Vidyaratne, Thomas Britton, Kishansingh Rajput, Malachi Schram, Sarah Cousineau
2021	A	`conf`	Enabling long-range exploration in minimization of multimodal functions. UAI Jiaxin Zhang, Hoang Tran, Dan Lu, Guannan Zhang
2021	J	`jnl`	PI3NN: Prediction intervals from three independently trained neural networks. CoRR Siyan Liu, Pei Zhang, Dan Lu, Guannan Zhang
2020	J	`jnl`	A Scalable Evolution Strategy with Directional Gaussian Smoothing for Blackbox Optimization. CoRR Jiaxin Zhang, Hoang Tran, Dan Lu, Guannan Zhang
2020	—	`conf`	Efficient Distance-based Global Sensitivity Analysis for Terrestrial Ecosystem Modeling. ICDM (Workshops) Dan Lu, Daniel M. Ricciuto
2019	—	`conf`	An Efficient Bayesian Method for Advancing the Application of Deep Learning in Earth Science. ICDM Workshops Dan Lu, Siyan Liu, Daniel M. Ricciuto
2019	J	`jnl`	An adaptive Kriging surrogate method for efficient uncertainty quantification with an application to geological carbon sequestration modeling. Comput. Geosci. Shaoxing Mo, Xiaoqing Shi, Dan Lu, Ming Ye, Jichun Wu
2019	J	`jnl`	Efficient surrogate modeling methods for large-scale Earth system models based on machine learning techniques. CoRR Dan Lu, Daniel M. Ricciuto
2019	—	`conf`	Learning-Based Inversion-Free Model-Data Integration to Advance Ecosystem Model Prediction. ICDM Workshops Dan Lu, Daniel M. Ricciuto
2014	J	`jnl`	A computer program for uncertainty analysis integrating regression and Bayesian methods. Environ. Model. Softw. Dan Lu, Ming Ye, Mary C. Hill, Eileen P. Poeter, Gary P. Curtis