most citedOn Deriving Probabilistic Models for Adsorption Energy on Transition Metals using Multi-level Ab initio and Experimental Data

5 citations · 7 across the 3 of their papers we have counts for

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physics.data-an2019★ 2 cited

Designing compact training sets for data-driven molecular property prediction

Bowen Li, Srinivas Rangarajan

In this paper, we consider the problem of designing a training set using the most informative molecules from a specified library to build data-driven molecular property models. Spe…

physics.data-an2019★ 5 cited

On Deriving Probabilistic Models for Adsorption Energy on Transition Metals using Multi-level Ab initio and Experimental Data

Huijie Tian, Srinivas Rangarajan

In this paper, we apply multi-task Gaussian Process (MT-GP) to show that the adsorption energy of small adsorbates on transition metal surfaces can be modeled to a high level of fi…