The PMNLV model extends single-neuron overdispersion to populations via matrix-normal gain priors, showing shared co-variability highest in V1 and declining along the mouse visual hierarchy.
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7 Pith papers cite this work. Polarity classification is still indexing.
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PINN-AFE uses multi-head attention and input convex networks to solve Monge-Ampère equations with claimed accuracy, efficiency, and extensions to image enhancement and medical registration.
An SDP-based framework computes optimal quantum cloning maps via Choi isomorphism, certifies optimality with duality, and extracts Kraus operators for universal, phase-covariant, asymmetric, and entanglement cloning including higher-order cases.
Establishes n^{1-ε}-hardness of approximation for dichromatic number and acyclic number on tournaments, plus polynomial-time approximations for ℓ-dicolorable digraphs and special dense cases.
Gaussian randomized rounding on two-qubit marginals of depth-D circuits with local depolarizing noise p yields samples whose expected Max-Cut cost matches the noisy quantum device up to an approximation ratio of 1-O[(1-p)^D].
A column generation method with interior-point SDP solvers solves the continuous relaxation of exact D-optimal experimental design to identify support and construct near-optimal exact designs for large-scale instances.
A unified framework for determinant dynamics under low-rank perturbations is developed that extends to singular matrices via pseudodeterminant and provides multiplicative decompositions for controllability Gramians.
citing papers explorer
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Partitioning Neural Co-Variability
The PMNLV model extends single-neuron overdispersion to populations via matrix-normal gain priors, showing shared co-variability highest in V1 and declining along the mouse visual hierarchy.
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Physics-Informed Neural Networks with Attention Feature Expansion for Monge-Amp\`ere Equations
PINN-AFE uses multi-head attention and input convex networks to solve Monge-Ampère equations with claimed accuracy, efficiency, and extensions to image enhancement and medical registration.
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Semidefinite Programming for Optimal Quantum Cloning: A Computational Framework
An SDP-based framework computes optimal quantum cloning maps via Choi isomorphism, certifies optimality with duality, and extracts Kraus operators for universal, phase-covariant, asymmetric, and entanglement cloning including higher-order cases.
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Hardness and Approximation for Coloring Digraphs
Establishes n^{1-ε}-hardness of approximation for dichromatic number and acyclic number on tournaments, plus polynomial-time approximations for ℓ-dicolorable digraphs and special dense cases.
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Sampling (noisy) quantum circuits through randomized rounding
Gaussian randomized rounding on two-qubit marginals of depth-D circuits with local depolarizing noise p yields samples whose expected Max-Cut cost matches the noisy quantum device up to an approximation ratio of 1-O[(1-p)^D].
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A column generation approach to exact experimental design
A column generation method with interior-point SDP solvers solves the continuous relaxation of exact D-optimal experimental design to identify support and construct near-optimal exact designs for large-scale instances.
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Determinant Dynamics under Low-Rank Perturbations: A Unified Framework for Singular Systems
A unified framework for determinant dynamics under low-rank perturbations is developed that extends to singular matrices via pseudodeterminant and provides multiplicative decompositions for controllability Gramians.