Dongxia Wu

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 18

Top Topics

Diffusion Model

Stochastic Simulation

Spatiotemporal Databases

Top Venues

Publications

Dongxia Wu, Tsuyoshi Idé, Aurélie C. Lozano, Georgios Kollias, Jirí Navrátil, Naoki Abe, Yi-An Ma, Rose Yu
Learning Granger Causality from Instance-wise Self-attentive Hawkes Processes. CoRR (2024)
Peter Eckmann, Dongxia Wu, Germano Heinzelmann, Michael K. Gilson, Rose Yu
MFBind: a Multi-Fidelity Approach for Evaluating Drug Compounds in Practical Generative Modeling. CoRR (2024)
Ruijia Niu, Dongxia Wu, Kai Kim, Yi-An Ma, Duncan Watson-Parris, Rose Yu
Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling. CoRR (2024)
Dongxia Wu, Nikki Lijing Kuang, Ruijia Niu, Yi-An Ma, Rose Yu
Diff-BBO: Diffusion-Based Inverse Modeling for Black-Box Optimization. CoRR (2024)
Lingkai Kong, Yuanqi Du, Wenhao Mu, Kirill Neklyudov, Valentin De Bortol, Haorui Wang, Dongxia Wu, Aaron Ferber, Yi-An Ma, Carla P. Gomes, Chao Zhang
Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints. CoRR (2024)
Dongxia Wu, Tsuyoshi Idé, Georgios Kollias, Jirí Navrátil, Aurélie C. Lozano, Naoki Abe, Yi-An Ma, Rose Yu
Learning Granger Causality from Instance-wise Self-attentive Hawkes Processes. AISTATS (2024)
Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Yian Ma, Rose Yu
Disentangled Multi-Fidelity Deep Bayesian Active Learning. ICML (2023)
Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
Deep Bayesian Active Learning for Accelerating Stochastic Simulation. KDD (2023)
Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Yian Ma, Rose Yu
Disentangled Multi-Fidelity Deep Bayesian Active Learning. CoRR (2023)
Dongxia Wu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
Multi-fidelity Hierarchical Neural Processes. CoRR (2022)
Dongxia Wu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
Multi-fidelity Hierarchical Neural Processes. KDD (2022)
Utkrisht Rajkumar, Sara Javadzadeh, Mihir Bafna, Dongxia Wu, Rose Yu, Jingbo Shang, Vineet Bafna
DeepViFi: detecting oncoviral infections in cancer genomes using transformers. BCB (2022)
Dongxia Wu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
Accelerating Stochastic Simulation with Interactive Neural Processes. CoRR (2021)
Mingren Shen, Guanzhao Li, Dongxia Wu, Yudai Yaguchi, Jack C. Haley, Kevin G. Field, Dane Morgan
A Deep Learning Based Automatic Defect Analysis Framework for In-situ TEM Ion Irradiations. CoRR (2021)
Dongxia Wu, Liyao Gao, Matteo Chinazzi, Xinyue Xiong, Alessandro Vespignani, Yi-An Ma, Rose Yu
Quantifying Uncertainty in Deep Spatiotemporal Forecasting. KDD (2021)
Mingren Shen, Guanzhao Li, Dongxia Wu, Yuhan Liu, Jacob Greaves, Wei Hao, Nathaniel J. Krakauer, Leah Krudy, Jacob Perez, Varun Sreenivasan, Bryan Sanchez, Oigimer Torres, Wei Li, Kevin Field, Dane Morgan
Multi defect detection and analysis of electron microscopy images with deep learning. CoRR (2021)
Dongxia Wu, Liyao Gao, Xinyue Xiong, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
Quantifying Uncertainty in Deep Spatiotemporal Forecasting. CoRR (2021)
Dongxia Wu, Liyao Gao, Xinyue Xiong, Matteo Chinazzi, Alessandro Vespignani, Yian Ma, Rose Yu
DeepGLEAM: a hybrid mechanistic and deep learning model for COVID-19 forecasting. CoRR (2021)