44 citations · 143 across the 17 of their papers we have counts for
6 papers · 1 filter
Grokking Explained: A Statistical Phenomenon
Breno W. Carvalho, Artur S. d'Avila Garcez, Luís C. Lamb +1
Grokking, or delayed generalization, is an intriguing learning phenomenon where test set loss decreases sharply only after a model's training set loss has converged. This challenge…
A Large Encoder-Decoder Family of Foundation Models For Chemical Language
Eduardo Soares, Victor Shirasuna, Emilio Vital Brazil +3
Large-scale pre-training methodologies for chemical language models represent a breakthrough in cheminformatics. These methods excel in tasks such as property prediction and molecu…
Improving Molecular Properties Prediction Through Latent Space Fusion
Eduardo Soares, Akihiro Kishimoto, Emilio Vital Brazil +3
Pre-trained Language Models have emerged as promising tools for predicting molecular properties, yet their development is in its early stages, necessitating further research to enh…
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…
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…
Netherlands Dataset: A New Public Dataset for Machine Learning in Seismic Interpretation
Reinaldo Mozart Silva, Lais Baroni, Rodrigo S. Ferreira +3
Machine learning and, more specifically, deep learning algorithms have seen remarkable growth in their popularity and usefulness in the last years. This is arguably due to three ma…