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07/11/2023
Predicting small molecules solubilities on endpoint devices using deep ensemble neural networks
Aqueous solubility is a valuable yet challenging property to predict. Co...
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06/09/2023
14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon
Chemistry and materials science are complex. Recently, there have been g...
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05/17/2023
Active Learning in Symbolic Regression with Physical Constraints
Evolutionary symbolic regression (SR) fits a symbolic equation to data, ...
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04/20/2023
Censoring chemical data to mitigate dual use risk
The dual use of machine learning applications, where models can be used ...
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04/11/2023
ChemCrow: Augmenting large-language models with chemistry tools
Large-language models (LLMs) have recently shown strong performance in t...
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04/11/2023
Bayesian Optimization of Catalysts With In-context Learning
Large language models (LLMs) are able to do accurate classification with...
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02/07/2023
Recent advances in the Self-Referencing Embedding Strings (SELFIES) library
String-based molecular representations play a crucial role in cheminform...
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08/12/2021
City-wide modeling of Vehicle-to-Grid Economics to Understand Effects of Battery Performance
Vehicle-to-grid (V2G) is a promising approach to solve the problem of gr...
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04/19/2021
Simulation-Based Inference with Approximately Correct Parameters via Maximum Entropy
Inferring the input parameters of simulators from observations is a cruc...
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11/20/2019
Iterative Peptide Modeling With Active Learning And Meta-Learning
Often the development of novel materials is not amenable to high-through...
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04/17/2018
