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- IBM (United States)US73 papers
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27 papers · 1 filter
Membership Inference Attacks as Privacy Tools: Reliability, Disparity and Ensemble
Zhiqi Wang, Chengyu Zhang, Yuetian Chen +3
Membership inference attacks (MIAs) pose a significant threat to the privacy of machine learning models and are widely used as tools for privacy assessment, auditing, and machine u…
Improving Electrolyte Performance for Target Cathode Loading Using Interpretable Data-Driven Approach
Vidushi Sharma, Andy Tek, Khanh Nguyen +4
Higher loading of active electrode materials is desired in batteries, especially those based on conversion reactions, for enhanced energy density and cost efficiency. However, incr…
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…
Incorporating Experts' Judgment into Machine Learning Models
Hogun Park, Aly Megahed, Peifeng Yin +3
Machine learning (ML) models have been quite successful in predicting outcomes in many applications. However, in some cases, domain experts might have a judgment about the expected…
Fusing Modalities by Multiplexed Graph Neural Networks for Outcome Prediction in Tuberculosis
Niharika S. D'Souza, Hongzhi Wang, Andrea Giovannini +4
In a complex disease such as tuberculosis, the evidence for the disease and its evolution may be present in multiple modalities such as clinical, genomic, or imaging data. Effectiv…
Accelerating Material Design with the Generative Toolkit for Scientific Discovery
Matteo Manica, Jannis Born, Joris Cadow +21
With the growing availability of data within various scientific domains, generative models hold enormous potential to accelerate scientific discovery. They harness powerful represe…