4 citations · 7 across the 7 of their papers we have counts for
7 papers
Beyond Chemical Language: A Multimodal Approach to Enhance Molecular Property Prediction
Eduardo Soares, Emilio Vital Brazil, Karen Fiorela Aquino Gutierrez +4
We present a novel multimodal language model approach for predicting molecular properties by combining chemical language representation with physicochemical features. Our approach,…
Retrospective End-User Walkthrough: A Method for Assessing How People Combine Multiple AI Models in Decision-Making Systems
Vagner Figueredo de Santana, Larissa Monteiro Da Fonseca Galeno, Emilio Vital Brazil +2
Evaluating human-AI decision-making systems is an emerging challenge as new ways of combining multiple AI models towards a specific goal are proposed every day. As humans interact…
Human-AI Co-Creation Approach to Find Forever Chemicals Replacements
Juliana Jansen Ferreira, Vinícius Segura, Joana G. R. Souza +4
Generative models are a powerful tool in AI for material discovery. We are designing a software framework that supports a human-AI co-creation process to accelerate finding replace…
Position Paper on Dataset Engineering to Accelerate Science
Emilio Vital Brazil, Eduardo Soares, Lucas Villa Real +4
Data is a critical element in any discovery process. In the last decades, we observed exponential growth in the volume of available data and the technology to manipulate it. Howeve…
Knowledge-augmented Risk Assessment (KaRA): a hybrid-intelligence framework for supporting knowledge-intensive risk assessment of prospect candidates
Carlos Raoni Mendes, Emilio Vital Brazil, Vinicius Segura +1
Evaluating the potential of a prospective candidate is a common task in multiple decision-making processes in different industries. We refer to a prospect as something or someone t…
Toward Human-AI Co-creation to Accelerate Material Discovery
Dmitry Zubarev, Carlos Raoni Mendes, Emilio Vital Brazil +5
There is an increasing need in our society to achieve faster advances in Science to tackle urgent problems, such as climate changes, environmental hazards, sustainable energy syste…
Managing Data Lineage of O&G Machine Learning Models: The Sweet Spot for Shale Use Case
Raphael Thiago, Renan Souza, L. Azevedo +7
Machine Learning (ML) has increased its role, becoming essential in several industries. However, questions around training data lineage, such as "where has the dataset used to trai…