Modeling and Design Optimization of Loosely Coupled PCB Spiral Coils in Inductive Power Transfer Systems

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In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

We develop new tools to study landscapes in nonconvex optimization. Given one optimization problem, we pair it with another by smoothly parametrizing the domain. This is either for practical purposes (e.g., to use smooth optimization algorithms with good g ...

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Despite the widespread empirical success of ResNet, the generalization properties of deep ResNet are rarely explored beyond the lazy training regime. In this work, we investigate scaled ResNet in the limit of infinitely deep and wide neural networks, of wh ...

Time-domain solutions of Maxwell’s equations in homogeneous and isotropic media are paramount to studying transient or broadband phenomena. However, analytical solutions are generally unavailable for practical applications, while numerical solutions are co ...

Orthogonal group synchronization is the problem of estimating n elements Z(1),& mldr;,Z(n) from the rxr orthogonal group given some relative measurements R-ij approximate to Z(i)Z(j)(-1). The least-squares formulation is nonconvex. To avoid its local minim ...

Time reversal exploits the invariance of electromagnetic wave propagation in reciprocal and lossless media to localize radiating sources. Time-reversed measurements are back-propagated in a simulated domain and converge to the unknown source location. The ...

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In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

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Many feedforward neural networks (NNs) generate continuous and piecewise-linear (CPWL) mappings. Specifically, they partition the input domain into regions on which the mapping is affine. The number of these so-called linear regions offers a natural metric ...

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Modeling and Design Optimization of Loosely Coupled PCB Spiral Coils in Inductive Power Transfer Systems

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Random matrix methods for high-dimensional machine learning models

The effect of smooth parametrizations on nonconvex optimization landscapes

Precision luminosity measurement at hadron colliders

Generalization of Scaled Deep ResNets in the Mean-Field Regime

The time-domain Cartesian multipole expansion of electromagnetic fields

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Spatiotemporal energy‐density distribution of time‐reversed electromagnetic fields

Safe Deep Neural Networks

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Efficient and insightful descriptors for representing molecular and material space

On the number of regions of piecewise linear neural networks

Integrated Wireless Power, Data Communication, and Thermal Sensing System for Autonomous Multisite Brain Implants