Training hybrid neural networks with multimode optical nonlinearities using digital twins

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Reinforcement learning (RL) is inherently rife with non-stationarity since the states and rewards the agent observes during training depend on its changing policy. Therefore, networks in deep RL must be capable of adapting to new observations and fitting n ...

Photonic integrated circuit optical waveguide device preparation or fabrication method comprising providing a silicon substrate, depositing at least one copper gettering silicon nitride layer or material, depositing at least one optical waveguide cladding ...

Recent decades have seen significant advancements in integrated photonics, driven by improvements in nanofabrication technology. This field has been developed from integrated semiconductor lasers and low-loss waveguides to optical modulators, enabling the ...

We investigate popular resampling methods for estimating the uncertainty of statistical models, such as subsampling, bootstrap and the jackknife, and their performance in high-dimensional supervised regression tasks. We provide a tight asymptotic descripti ...

Fourier ptychography (FP) involves the acquisition of several low-resolution intensity images of a sample under varying illumination angles. They are then combined into a high-resolution complex-valued image by solving a phase-retrieval problem. The object ...

The stochastic block model (SBM) is widely studied as a benchmark for graph clustering aka community detection. In practice, graph data often come with node attributes that bear additional information about the communities. Previous works modeled such data ...

Training hybrid neural networks with multimode optical nonlinearities using digital twins

Chattez avec Graph Search

No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO

Photonic substrate preparation method and photonic waveguide preparation or fabrication method

Piezoelectric actuation for integrated photonics

Analysis of Bootstrap and Subsampling in High-dimensional Regularized Regression

Dynamic Fourier ptychography with deep spatiotemporal priors

Neural-prior stochastic block model