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MFBind: a Multi-Fidelity Approach for Evaluating Drug Compounds in Practical Generative Modeling.

P. Eckmann, D. Wu, G. Heinzelmann, M. Gilson, and R. Yu. CoRR, (2024)

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Jinglan Wu

Recovery of citric acid from fermentation broth using simulated moving bed technology: = Reinigung von Zitronensäure aus Fermentationslösung durch kontinuierliche ChromatographieJ. Wu. Uni Erlangen-Nürnberg, (2009)

Jinjin Wu

Yinghua Wu

Changzhu Wu

Haiyan Wu

Other publications of authors with the same name

MFBind: a Multi-Fidelity Approach for Evaluating Drug Compounds in Practical Generative Modeling.P. Eckmann, D. Wu, G. Heinzelmann, M. Gilson, and R. Yu. CoRR, (2024)Deep Bayesian Active Learning for Accelerating Stochastic Simulation.D. Wu, R. Niu, M. Chinazzi, A. Vespignani, Y. Ma, and R. Yu. KDD, page 2559-2569. ACM, (2023)Disentangled Multi-Fidelity Deep Bayesian Active Learning.D. Wu, R. Niu, M. Chinazzi, Y. Ma, and R. Yu. ICML, volume 202 of Proceedings of Machine Learning Research, page 37624-37634. PMLR, (2023)Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints.L. Kong, Y. Du, W. Mu, K. Neklyudov, V. Bortol, H. Wang, D. Wu, A. Ferber, Y. Ma, C. Gomes and 1 other author(s). CoRR, (2024)DeepGLEAM: a hybrid mechanistic and deep learning model for COVID-19 forecasting.D. Wu, L. Gao, X. Xiong, M. Chinazzi, A. Vespignani, Y. Ma, and R. Yu. CoRR, (2021)Multi-fidelity Hierarchical Neural Processes.D. Wu, M. Chinazzi, A. Vespignani, Y. Ma, and R. Yu. KDD, page 2029-2038. ACM, (2022)A Deep Learning Based Automatic Defect Analysis Framework for In-situ TEM Ion Irradiations.M. Shen, G. Li, D. Wu, Y. Yaguchi, J. Haley, K. Field, and D. Morgan. CoRR, (2021)Accelerating Stochastic Simulation with Interactive Neural Processes.D. Wu, M. Chinazzi, A. Vespignani, Y. Ma, and R. Yu. CoRR, (2021)Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling.R. Niu, D. Wu, K. Kim, Y. Ma, D. Watson-Parris, and R. Yu. CoRR, (2024)Learning Granger Causality from Instance-wise Self-attentive Hawkes Processes.D. Wu, T. Idé, G. Kollias, J. Navrátil, A. Lozano, N. Abe, Y. Ma, and R. Yu. AISTATS, volume 238 of Proceedings of Machine Learning Research, page 415-423. PMLR, (2024)

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Disambiguation of "Wu, Dongxia"

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MFBind: a Multi-Fidelity Approach for Evaluating Drug Compounds in Practical Generative Modeling.

Please choose a person to relate this publication to

Jinglan Wu

Jinjin Wu

Yinghua Wu

Changzhu Wu

Haiyan Wu

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Wu, Dongxia"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML MFBind: a Multi-Fidelity Approach for Evaluating Drug Compounds in Practical Generative Modeling.

Please choose a person to relate this publication to

Jinglan Wu

Jinjin Wu

Yinghua Wu

Changzhu Wu

Haiyan Wu

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
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MFBind: a Multi-Fidelity Approach for Evaluating Drug Compounds in Practical Generative Modeling.