Andrew D White | DeepAI

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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...

0 Mayk Caldas Ramos, et al. ∙

∙ 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...

1 Kevin Maik Jablonka, et al. ∙

∙ 05/17/2023

Active Learning in Symbolic Regression with Physical Constraints

Evolutionary symbolic regression (SR) fits a symbolic equation to data, ...

0 Jorge Medina, et al. ∙

∙ 04/20/2023

Censoring chemical data to mitigate dual use risk

The dual use of machine learning applications, where models can be used ...

0 Quintina L. Campbell, et al. ∙

∙ 04/11/2023

ChemCrow: Augmenting large-language models with chemistry tools

Large-language models (LLMs) have recently shown strong performance in t...

8 Andres M Bran, et al. ∙

∙ 04/11/2023

Bayesian Optimization of Catalysts With In-context Learning

Large language models (LLMs) are able to do accurate classification with...

0 Mayk Caldas Ramos, et al. ∙

∙ 02/07/2023

Recent advances in the Self-Referencing Embedding Strings (SELFIES) library

String-based molecular representations play a crucial role in cheminform...

0 Alston Lo, et al. ∙

∙ 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...

0 Heta A. Gandhi, et al. ∙

∙ 04/19/2021

Simulation-Based Inference with Approximately Correct Parameters via Maximum Entropy

Inferring the input parameters of simulators from observations is a cruc...

0 Rainier Barrett, et al. ∙

∙ 11/20/2019

Iterative Peptide Modeling With Active Learning And Meta-Learning

Often the development of novel materials is not amenable to high-through...

0 Rainier Barrett, et al. ∙

∙ 04/17/2018

Classifying Antimicrobial and Multifunctional Peptides with Bayesian Network Models

Bayesian network models are finding success in characterizing enzyme-cat...

0 Rainier Barrett, et al. ∙

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