Results 71 to 80 of about 10,590 (247)
Improving generalization and trainability of quantum eigensolvers via graph neural encoding
Machine Learning: Science and TechnologyDetermining the ground state of a many-body Hamiltonian is a central problem across physics, chemistry, and combinatorial optimization, yet it is often classically intractable due to the exponential growth of Hilbert space with system size. Even on fault-
Jungyun Lee, Daniel K Park
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Remarks on perspective simplices [PDF]
FME Transactions, 2017 The planar figure of two triangles being in perspective position is associated with a theorem of Desargues, which is responsible for the fact that the coordinate set of the plane is a field.
Weiss Gunter, Ebisui H.
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Limit T-subspaces and the central polynomials in n variables of the Grassmann algebra
Journal of Algebra, 2012 22 ...
Gonçalves, Dimas José +2 more
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Advanced Intelligent Discovery, EarlyView.This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
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Advanced Intelligent Discovery, EarlyView.Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez +4 more
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Advanced Intelligent Discovery, EarlyView.This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath +4 more
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Advanced Intelligent Discovery, EarlyView.Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi +2 more
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Successive direction extraction for estimating the central subspace in a multiple-index regression
Journal of Multivariate Analysis, 2008 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yin, Xiangrong +2 more
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Robust Representation Learning for Clean Feature Discovery in Incomplete Multi‐View Clustering
Advanced Intelligent Systems, EarlyView.Robust feature discovery in incomplete multi‐view clustering is achieved by coupling RPCA‐based clean representation recovery with neural‐network‐assisted graph learning. The resulting RIMVC framework constructs cleaner and more discriminative graph‐structured representations from incomplete and noisy multi‐view data, improving clustering robustness ...
Ping Hu +4 more
wiley +1 more source
Fragmentation, Zero Modes, and Collective Bound States in Constrained Models
PRX QuantumKinetically constrained models were originally introduced to capture slow relaxation in glassy systems, where dynamics are hindered by local constraints instead of energy barriers.
Eloi Nicolau +2 more
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