Researchers at Clarkson University are advancing the use of artificial intelligence and computational physics to accelerate ...
A new framework allows AI models that have already been trained to learn new tasks without sacrificing performance when ...
A context graph could capture the full context, reasoning, and causal relationships behind critical business decisions. It’s ...
What are the first steps that chart the path for a cell to become a blood cell, neuron cell, or pigment cell? Scientists have ...
Ligand-based drug design combines AI and QSAR modeling to prioritize drug candidates, minimizing preclinical failures and ...
You will be redirected to our submission process. Cancer tumorigenesis is fundamentally driven by the profound dysregulation of gene regulatory networks (GRNs) and complex epigenetic alterations. With ...
MFCN-DDI: Capsule network based on multimodal feature for multitype drug–drug interaction prediction
In modern medical systems, drug therapy remains one of the most essential approaches for disease prevention and treatment. In particular, combination ...
Abstract: Privacy-preserving deep learning is crucial for computational social systems such as healthcare and finance, where sensitive high-dimensional data (e.g ...
Abstract: We propose to learn the time-varying stochastic computational resource usage of software as a graph-structured Schrödinger bridge problem (SBP). In general, learning the computational ...
The Perspective by Tiwary et al. (8) offers a comprehensive overview of generative AI methods in computational chemistry. Approaches that generate new outputs (e.g., inferring phase transitions) by ...
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