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Found 3 papers, 3 papers with code
Predicting small molecules solubilities on endpoint devices using deep ensemble neural networks
Additionally, ease of use remains a concern for any computational technique, resulting in the sustained popularity of group-based contribution methods.
14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon
Recent studies suggested that these models could be useful in chemistry and materials science.
Bayesian Optimization of Catalysts With In-context Learning
We show a prompting system that enables regression with uncertainty for in-context learning with frozen LLM (GPT-3, GPT-3. 5, and GPT-4) models, allowing predictions without features or architecture tuning.
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