Dongxia Wu

27 papers A* 6A 2Journal 18Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
CellFluxRL: Biologically-Constrained Virtual Cell Modeling via Reinforcement Learning.
CoRR
Dongxia Wu, Shiye Su, Yuhui Zhang, Elaine Sui, Emma Lundberg, Emily B. Fox, Serena Yeung-Levy
2026 J jnl
Divide and Learn: Multi-Objective Combinatorial Optimization at Scale.
CoRR
Esha Singh, Dongxia Wu, Chien-Yi Yang, Tajana Rosing, Rose Yu, Yi-An Ma
2026 J jnl
Uncertainty Quantification for Distribution-to-Distribution Flow Matching in Scientific Imaging.
CoRR
Dongxia Wu, Yuhui Zhang, Serena Yeung-Levy, Emma Lundberg, Emily B. Fox
2025 A conf
Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints.
AISTATS
Lingkai Kong, Yuanqi Du, Wenhao Mu, Kirill Neklyudov, Valentin De Bortoli, Dongxia Wu, Haorui Wang, Aaron M. Ferber, Yian Ma, Carla P. Gomes, Chao Zhang
2025 A* conf
MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning.
ICML
Peter Eckmann, Dongxia Wu, Germano Heinzelmann, Michael K. Gilson, Rose Yu
2025 J jnl
SimulRAG: Simulator-based RAG for Grounding LLMs in Long-form Scientific QA.
CoRR
Haozhou Xu, Dongxia Wu, Matteo Chinazzi, Ruijia Niu, Rose Yu, Yi-An Ma
2024 J jnl
Diff-BBO: Diffusion-Based Inverse Modeling for Black-Box Optimization.
CoRR
Dongxia Wu, Nikki Lijing Kuang, Ruijia Niu, Yi-An Ma, Rose Yu
2024 J jnl
Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints.
CoRR
Lingkai Kong, Yuanqi Du, Wenhao Mu, Kirill Neklyudov, Valentin De Bortoli, Haorui Wang, Dongxia Wu, Aaron M. Ferber, Yi-An Ma, Carla P. Gomes, Chao Zhang
2024 J jnl
Functional-level Uncertainty Quantification for Calibrated Fine-tuning on LLMs.
CoRR
Ruijia Niu, Dongxia Wu, Rose Yu, Yi-An Ma
2024 A conf
Learning Granger Causality from Instance-wise Self-attentive Hawkes Processes.
AISTATS
Dongxia Wu, Tsuyoshi Idé, Georgios Kollias, Jirí Navrátil, Aurélie C. Lozano, Naoki Abe, Yi-An Ma, Rose Yu
2024 J jnl
Learning Granger Causality from Instance-wise Self-attentive Hawkes Processes.
CoRR
Dongxia Wu, Tsuyoshi Idé, Aurélie C. Lozano, Georgios Kollias, Jirí Navrátil, Naoki Abe, Yi-An Ma, Rose Yu
2024 J jnl
MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning.
CoRR
Peter Eckmann, Dongxia Wu, Germano Heinzelmann, Michael K. Gilson, Rose Yu
2024 J jnl
MFBind: a Multi-Fidelity Approach for Evaluating Drug Compounds in Practical Generative Modeling.
CoRR
Peter Eckmann, Dongxia Wu, Germano Heinzelmann, Michael K. Gilson, Rose Yu
2024 A* conf
Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling.
ICML
Ruijia Niu, Dongxia Wu, Kai Kim, Yian Ma, Duncan Watson-Parris, Rose Yu
2024 J jnl
Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling.
CoRR
Ruijia Niu, Dongxia Wu, Kai Kim, Yi-An Ma, Duncan Watson-Parris, Rose Yu
2023 A* conf
Deep Bayesian Active Learning for Accelerating Stochastic Simulation.
KDD
Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
2023 A* conf
Disentangled Multi-Fidelity Deep Bayesian Active Learning.
ICML
Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Yi-An Ma, Rose Yu
2023 J jnl
Disentangled Multi-Fidelity Deep Bayesian Active Learning.
CoRR
Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Yi-An Ma, Rose Yu
2022 — conf
DeepViFi: detecting oncoviral infections in cancer genomes using transformers.
BCB
Utkrisht Rajkumar, Sara Javadzadeh, Mihir Bafna, Dongxia Wu, Rose Yu, Jingbo Shang, Vineet Bafna
2022 A* conf
Multi-fidelity Hierarchical Neural Processes.
KDD
Dongxia Wu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
2022 J jnl
Multi-fidelity Hierarchical Neural Processes.
CoRR
Dongxia Wu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
2021 J jnl
A Deep Learning Based Automatic Defect Analysis Framework for In-situ TEM Ion Irradiations.
CoRR
Mingren Shen, Guanzhao Li, Dongxia Wu, Yudai Yaguchi, Jack C. Haley, Kevin G. Field, Dane Morgan
2021 J jnl
Accelerating Stochastic Simulation with Interactive Neural Processes.
CoRR
Dongxia Wu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
2021 J jnl
DeepGLEAM: a hybrid mechanistic and deep learning model for COVID-19 forecasting.
CoRR
Dongxia Wu, Liyao Gao, Xinyue Xiong, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
2021 J jnl
Multi defect detection and analysis of electron microscopy images with deep learning.
CoRR
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
2021 A* conf
Quantifying Uncertainty in Deep Spatiotemporal Forecasting.
KDD
Dongxia Wu, Liyao Gao, Matteo Chinazzi, Xinyue Xiong, Alessandro Vespignani, Yi-An Ma, Rose Yu
2021 J jnl
Quantifying Uncertainty in Deep Spatiotemporal Forecasting.
CoRR
Dongxia Wu, Liyao Gao, Xinyue Xiong, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu