no code implementations • 8 Dec 2023 • Jakub Lála, Odhran O'Donoghue, Aleksandar Shtedritski, Sam Cox, Samuel G. Rodriques, Andrew D. White
We present PaperQA, a RAG agent for answering questions over the scientific literature.
1 code implementation • 11 Jul 2023 • Mayk Caldas Ramos, Andrew D. White
Additionally, ease of use remains a concern for any computational technique, resulting in the sustained popularity of group-based contribution methods.
2 code implementations • 9 Jun 2023 • Kevin Maik Jablonka, Qianxiang Ai, Alexander Al-Feghali, Shruti Badhwar, Joshua D. Bocarsly, Andres M Bran, Stefan Bringuier, L. Catherine Brinson, Kamal Choudhary, Defne Circi, Sam Cox, Wibe A. de Jong, Matthew L. Evans, Nicolas Gastellu, Jerome Genzling, María Victoria Gil, Ankur K. Gupta, Zhi Hong, Alishba Imran, Sabine Kruschwitz, Anne Labarre, Jakub Lála, Tao Liu, Steven Ma, Sauradeep Majumdar, Garrett W. Merz, Nicolas Moitessier, Elias Moubarak, Beatriz Mouriño, Brenden Pelkie, Michael Pieler, Mayk Caldas Ramos, Bojana Ranković, Samuel G. Rodriques, Jacob N. Sanders, Philippe Schwaller, Marcus Schwarting, Jiale Shi, Berend Smit, Ben E. Smith, Joren Van Herck, Christoph Völker, Logan Ward, Sean Warren, Benjamin Weiser, Sylvester Zhang, Xiaoqi Zhang, Ghezal Ahmad Zia, Aristana Scourtas, KJ Schmidt, Ian Foster, Andrew D. White, Ben Blaiszik
Recent studies suggested that these models could be useful in chemistry and materials science.
no code implementations • 17 May 2023 • Jorge Medina, Andrew D. White
Evolutionary symbolic regression (SR) fits a symbolic equation to data, which gives a concise interpretable model.
1 code implementation • 20 Apr 2023 • Quintina L. Campbell, Jonathan Herington, Andrew D. White
The dual use of machine learning applications, where models can be used for both beneficial and malicious purposes, presents a significant challenge.
1 code implementation • 11 Apr 2023 • Mayk Caldas Ramos, Shane S. Michtavy, Marc D. Porosoff, Andrew D. White
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.
1 code implementation • 7 Feb 2023 • Alston Lo, Robert Pollice, AkshatKumar Nigam, Andrew D. White, Mario Krenn, Alán Aspuru-Guzik
String-based molecular representations play a crucial role in cheminformatics applications, and with the growing success of deep learning in chemistry, have been readily adopted into machine learning pipelines.
2 code implementations • 24 Jun 2020 • Zhiheng Li, Geemi P. Wellawatte, Maghesree Chakraborty, Heta A. Gandhi, Chenliang Xu, Andrew D. White
The selection of coarse-grained (CG) mapping operators is a critical step for CG molecular dynamics (MD) simulation.
no code implementations • 20 Nov 2019 • Rainier Barrett, Andrew D. White
One way this method can be improved is by ensuring that each experiment provides the best improvement in both peptide properties and predictive modeling accuracy.
1 code implementation • 17 Apr 2018 • Rainier Barrett, Shaoyi Jiang, Andrew D. White
Bayesian network models are finding success in characterizing enzyme-catalyzed reactions, slow conformational changes, predicting enzyme inhibition, and genomics.