16 citations · 19 across the 7 of their papers we have counts for
7 papers
ProtoMedAgent: Multimodal Clinical Interpretability via Privacy-Aware Agentic Workflows
Alvaro Lopez Pellicer, Plamen Angelov, Marwan Bukhari +3
While interpretable prototype networks offer compelling case-based reasoning for clinical diagnostics, their raw continuous outputs lack the semantic structure required for medical…
Understanding Structural Representation in Foundation Models for Polymers
Nathaniel H. Park, Eduardo Soares, Victor Y. Shirasuna +3
From the relative scarcity of training data to the lack of standardized benchmarks, the creation of effective foundation models for polymers faces significant and multi-faceted cha…
Towards a Foundation Model for Partial Differential Equations Across Physics Domains
Eduardo Soares, Emilio Vital Brazil, Victor Shirasuna +2
We present PDE-FM, a modular foundation model for physics-informed machine learning that unifies spatial, spectral, and temporal reasoning across heterogeneous partial differential…
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…
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,…