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Classification-based pathway analysis using GPNet with novel P-value computation.
Brief Bioinform
November 2024
Center for Artificial Intelligence Research, Wake Forest University School of Medicine, Winston-Salem, NC 27101, United States.
Pathway analysis plays a critical role in bioinformatics, enabling researchers to identify biological pathways associated with various conditions by analyzing gene expression data. However, the rise of large, multi-center datasets has highlighted limitations in traditional methods like Over-Representation Analysis (ORA) and Functional Class Scoring (FCS), which struggle with low signal-to-noise ratios (SNR) and large sample sizes. To tackle these challenges, we use a deep learning-based classification method, Gene PointNet, and a novel $P$-value computation approach leveraging the confusion matrix to address pathway analysis tasks.
View Article and Find Full Text PDFExperimental Equivalence Checking of Quantum Circuits by Nonlocality.
Phys Rev Lett
December 2024
University of Science and Technology of China, CAS Key Laboratory of Quantum Information, Hefei 230026, People's Republic of China.
The quantum circuit model is the most widely used theoretical model for quantum computing. Therefore, determining whether two quantum circuits whose internal structures cannot be seen have the same functionality will be a fundamental problem in future quantum industries, which however turns out to be QMA-hard. Here, based on a photonic system we experimentally implement the equivalence checking of two unknown quantum circuits with real unitary matrix representations, where quantum nonlocality plays a key role and allows us to measure an "average-case" distance between the two quantum circuits very efficiently.
View Article and Find Full Text PDFMinimum Energy Conical Intersection Optimization Using DFT/MRCI(2).
J Chem Theory Comput
January 2025
Department of Chemistry and Biomolecular Sciences, University of Ottawa, Ottawa K1N 6N5,Canada.
The combined density functional theory and multireference configuration interaction (DFT/MRCI) method is a semiempirical electronic structure approach that is both computationally efficient and has predictive accuracy for the calculation of electronic excited states and for the simulation of electronic spectroscopies. However, given that the reference space is generated via a selected-CI procedure, a challenge arises in the construction of smooth potential energy surfaces. To address this issue, we treat the local discontinuities that arise as noise within the Gaussian progress regression framework and learn the surfaces by explicitly incorporating and optimizing a white-noise kernel.
View Article and Find Full Text PDFAbstract visual reasoning based on algebraic methods.
Sci Rep
January 2025
School of Computer Science and Technology, Donghua University, Shanghai, 201620, China.
Extracting high-order abstract patterns from complex high-dimensional data forms the foundation of human cognitive abilities. Abstract visual reasoning involves identifying abstract patterns embedded within composite images, considered a core competency of machine intelligence. Traditional neuro-symbolic methods often infer unknown objects through data fitting, without fully exploring the abstract patterns within composite images and the sequential sensitivity of visual sequences.
View Article and Find Full Text PDFNonadiabatic Quantum Dynamics of Molecules Scattering from Metal Surfaces.
J Chem Theory Comput
January 2025
Institute of Physics, University of Freiburg, Hermann-Herder-Strasse 3, 79104 Freiburg, Germany.
Nonadiabatic coupling between electrons and molecular motion at metal surfaces leads to energy dissipation and dynamic steering effects during chemical surface dynamics. We present a theoretical approach to the scattering of molecules from metal surfaces that incorporates all nonadiabatic and quantum nuclear effects due to the coupling of the molecular degrees of freedom to the electrons in the metal. This is achieved with the hierarchical equations of motion (HEOM) approach, combined with a matrix product state representation in twin space.
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