44 citations · 143 across the 17 of their papers we have counts for
17 papers
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…
SELF-BART : A Transformer-based Molecular Representation Model using SELFIES
Indra Priyadarsini, Seiji Takeda, Lisa Hamada +3
Large-scale molecular representation methods have revolutionized applications in material science, such as drug discovery, chemical modeling, and material design. With the rise of…
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…
Geo-Sketcher: Rapid 3D Geological Modeling using Geological and Topographic Map Sketches
Ronan Amorim, Emilio Vital Brazil, Faramarz Samavati +1
The construction of 3D geological models is an essential task in oil/gas exploration, development and production. However, it is a cumbersome, time-consuming and error-prone task m…
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,…