Mayk Caldas Ramos

According to our database, Mayk Caldas Ramos authored at least 4 papers between 2023 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A Review of Large Language Models and Autonomous Agents in Chemistry.

Mayk Caldas Ramos, Christopher J. Collison, Andrew D. White

CoRR, 2024

2023

Predicting small molecules solubilities on endpoint devices using deep ensemble neural networks.

Mayk Caldas Ramos, Andrew D. White

CoRR, 2023

14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon.

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 Rankovic, Samuel G. Rodriques, Jacob N. Sanders, Philippe Schwaller, Marcus Schwarting, Jiale Shi, Berend Smit, Ben E. Smith, Joren Van Heck, Christoph Völker, Logan T. Ward, Sean Warren, Benjamin Weiser, Sylvester Zhang, Xiaoqi Zhang, Ghezal Ahmad Zia, Aristana Scourtas, K. J. Schmidt, Ian T. Foster, Andrew D. White, Ben Blaiszik

CoRR, 2023

Bayesian Optimization of Catalysts With In-context Learning.

Mayk Caldas Ramos, Shane S. Michtavy, Marc D. Porosoff, Andrew D. White

CoRR, 2023