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Edwin V. Bonilla
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Edwin V. Bonilla11 visible / 11 total nodes / 25 links

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Co-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipWorks onAuthorshipWorks onWorks onWorks onAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipTopic signalTopic signalTopic signalTopic signalTopic signalTopic signalEdwin V. BonillaAEdwin V. BonillaResearcherArrow: A Foundation Model for Causal DiscoveryWArrow: A Foundation Mod...preprint / 2026Ryan ThompsonARyan ThompsonResearcherHe ZhaoAHe ZhaoResearcherDaniel M. SteinbergADaniel M. SteinbergResearcherMachine LearningTMachine Learning49008 worksAddressing Over-Smoothing in Graph Neural Networks via Deep SupervisionWAddressing Over-Smoothi...preprint / 2022Optimizing Sequential Experimental Design with Deep Reinforcement LearningWOptimizing Sequential E...preprint / 2022Sparse Gaussian Processes Revisited: Bayesian Approaches to Inducing-Variable ApproximationsWSparse Gaussian Process...preprint / 2021Gray-box inference for structured Gaussian process modelsWGray-box inference for ...preprint / 2016BORE: Bayesian Optimization by Density-Ratio EstimationWBORE: Bayesian Optimiza...preprint / 2021
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Edwin V. Bonilla

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PaperArrow: A Foundation Model for Causal DiscoveryAuthorship / preprint / 2026PersonRyan ThompsonCo-authorship / ResearcherPersonHe ZhaoCo-authorship / ResearcherPersonDaniel M. SteinbergCo-authorship / ResearcherTopicMachine LearningWorks on / 49008 worksPaperAddressing Over-Smoothing in Graph Neural Networks via Deep SupervisionAuthorship / preprint / 2022PaperOptimizing Sequential Experimental Design with Deep Reinforcement LearningAuthorship / preprint / 2022PaperSparse Gaussian Processes Revisited: Bayesian Approaches to Inducing-Variable ApproximationsAuthorship / preprint / 2021

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