Inference for stochastic differential equations driven by weighted sub-fractional Brownian motion using neural networks and the Euler approximation
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PI-AMFM: Permutation-Invariant Learning for Variable-Cardinality AM-FM Mode Decomposition in Biomedical Signal Analysis
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Neural Fourier Surrogates for Data Reuploading Quantum Neural Networks
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Block Optimism for Nonstationary Bandits with Latent Linear Dynamics
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Tolerance-Based Fairness Auditing: Violation Certification and Sensitivity Screening
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Initial condition recovery in nonlinear damped viscous photoacoustic tomography using a convolutional neural network-guided gradient-free optimization framework
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Polylogarithmic Sparsity of Randomly Reweighted NPMLEs for Gaussian Mixtures
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Classical Hardness of Learning Functions of Hamiltonians
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Continual Learning for 6-DoF Grasp Synthesis via Experience and Demonstrations
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Reachability-Informed Reinforcement Learning for Multi-Impulse Interplanetary Transfers
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