Search Results for author: Yousung Jung

Found 5 papers, 3 papers with code

Assessing the Extrapolation Capability of Template-Free Retrosynthesis Models

no code implementations29 Feb 2024 Shuan Chen, Yousung Jung

Despite the acknowledged capability of template-free models in exploring unseen reaction spaces compared to template-based models for retrosynthesis prediction, their ability to venture beyond established boundaries remains relatively uncharted.


A generalized-template-based graph neural network for accurate organic reactivity prediction

1 code implementation Nature Machine Intelligence 2022 Shuan Chen, Yousung Jung

In addition to the built-in interpretability of the generalized reaction templates, the high score–accuracy correlation of the model allows users to assess the uncertainty of the machine predictions.

Chemical Reaction Prediction

Deep Retrosynthetic Reaction Prediction using Local Reactivity and Global Attention

1 code implementation JACS Au 2021 Shuan Chen, Yousung Jung

Our model shows a promising 89. 5 and 99. 2% round-trip accuracy at top-1 and top-5 predictions for the USPTO-50K dataset containing 50 016 reactions.

Retrosynthesis Single-step retrosynthesis

Catalyst design using actively learned machine with non-ab initio input features towards CO2 reduction reactions

no code implementations14 Sep 2017 Juhwan Noh, JaeHoon Kim, Seoin Back, Yousung Jung

In conventional chemisorption model, the d-band center theory (augmented sometimes with the upper edge of d-band for imporved accuarcy) plays a central role in predicting adsorption energies and catalytic activity as a function of d-band center of the solid surfaces, but it requires density functional calculations that can be quite costly for large scale screening purposes of materials.

Active Learning

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