Results 71 to 80 of about 246 (200)
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
wiley +1 more source
HTFC gets 3D refractive index tomograms of flowing cells. Label‐free monocytes are engineered to express patterns of cytoplasmic vacuoles. From the tomogram, an efficient dimensionality reduction is operated. Interpretable features are extracted to classify the expression severity of phenotypes coexisting in each cell, visually represented by a seven ...
Marika Valentino +9 more
wiley +1 more source
Robust Representation Learning for Clean Feature Discovery in Incomplete Multi‐View Clustering
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
ABSTRACT We introduce a family of bosonic quantum error‐correcting codes built as a rotation‐symmetric superposition of squeezed vacuum states, which promise protection against both loss and dephasing noise channels. The robustness of these “squeezed‐vacuum codes” arises from being arranged at evenly spaced angles in phase‐space, and simultaneously in ...
Nir Gutman +4 more
wiley +1 more source
Fragmentation, Zero Modes, and Collective Bound States in Constrained Models
Kinetically 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
doaj +1 more source
Abstract Large swarms often adopt a hierarchical network structure that incorporates information aggregation. Although this approach offers significant advantages in terms of communication efficiency and computational complexity, it can also lead to degradation due to information constraints.
Kento Fujita, Daisuke Tsubakino
wiley +1 more source
Successive direction extraction for estimating the central subspace in a multiple-index regression
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yin, Xiangrong +2 more
openaire +1 more source
Machine Learning Paradigm for Advanced Battery Electrolyte Development
Electrolyte materials determine ion transport kinetics within the bulk and interphases, ultimately influencing the performance of battery systems. As data‐driven paradigms increasingly reshape materials discovery, this review provides an application‐oriented exploration of the intersection between machine learning and electrolyte science. By evaluating
Chang Su +4 more
wiley +1 more source
Test function: A new approach for covering the central subspace
In this paper we offer a complete methodology for sufficient dimension reduction called the test function (TF). TF provides a new family of methods for the estimation of the central subspace (CS) based on the introduction of a nonlinear transformation of the response.
Portier, François, Delyon, Bernard
openaire +2 more sources
ABSTRACT The leading‐order asymptotic behavior of the solution of the Cauchy initial‐value problem for the Benjamin–Ono equation in L2(R)$L^2(\mathbb {R})$ is obtained explicitly for generic rational initial data u0$u_0$. An explicit asymptotic wave profile uZD(t,x;ε)$u^\mathrm{ZD}(t,x;\epsilon)$ is given, in terms of the branches of the multivalued ...
Elliot Blackstone +3 more
wiley +1 more source

