Riemannian Geometry for Noise-Robust Covariance Network Analysis of Schizophrenia EEG: Geometric-Entropic Signatures of Dysconnectivity. [PDF]
Song R, He J, Wang J.
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Generative AI as a transformational logic for cognitive neuroscience. [PDF]
Beste C, Safavi S.
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What topological and geometric structure do biological foundation models learn? Evidence from 141 hypotheses. [PDF]
Kendiukhov I.
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LAIOR: a hyperbolic neural ODE variational framework for interpretable single-cell manifold learning and trajectory inference. [PDF]
Fu Z, Fu J, Zhang K, Ran T, Chen C.
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Noise-invariant representations of sound emerge along the canonical cortical hierarchy. [PDF]
Suarez Omedas T, Williamson RS.
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The representational geometry of naturalistic textures in macaque V1 and V2. [PDF]
Pavuluri A, Kohn A.
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Graph Topology Reframes the Coherence of Cell-State Manifold Inference under Heterogeneous Single-Cell Observations. [PDF]
Tamura T +4 more
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Sleep reveals dynamics integrating and segregating movement and stimulus representations in V1. [PDF]
de Oliveira EF +5 more
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Data field theory: a geometric framework for learning on Riemannian manifolds with synthetic validation and limitation analysis. [PDF]
Nehzati M.
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Beyond |E|2: Tensorial Electrostatic Reorganization in Hydrated Eu3+-Nitrate Complexes and Its Implications for Hypersensitive Luminescence. [PDF]
Marques MS.
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