Update on yesterday's dose-Use of delivery log-files for daily adaptive proton therapy (DAPT)

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We study the problem of performance optimization of closed -loop control systems with unmodeled dynamics. Bayesian optimization (BO) has been demonstrated to be effective for improving closed -loop performance by automatically tuning controller gains or re ...

We propose an adaptive quantum algorithm to prepare accurate variational time evolved wave functions. The method is based on the projected variational quantum dynamics (pVQD) algorithm, that performs a global optimization with linear scaling in the number ...

Electrical stimulation of the visual nervous system could improve the quality of life of patients affected by acquired blindness by restoring some visual sensations, but requires careful optimization of stimulation parameters to produce useful perceptions. ...

Diffusion-based generative methods have proven effective in modeling trajectories with offline datasets. However, they often face computational challenges and can falter in generalization, especially in capturing temporal abstractions for long- horizon tas ...

In this paper, we present a new parameterization and optimization procedure for minimizing the weight of ribbed plates. The primary goal is to reduce embodied CO2 in concrete floors as part of the effort to diminish the carbon footprint of the construction ...

Modern optimization is tasked with handling applications of increasingly large scale, chiefly due to the massive amounts of widely available data and the ever-growing reach of Machine Learning. Consequently, this area of research is under steady pressure t ...

This paper offers a new algorithm to efficiently optimize scheduling decisions for dial-a-ride problems (DARPs), including problem variants considering electric and autonomous vehicles (e-ADARPs). The scheduling heuristic, based on linear programming theor ...

The auxiliary power supply for medium voltage converters requires high insulation capability between the source and the load. Inductive power transfer technology, with an air gap between the primary and secondary coil, offers such high insulation capabilit ...

We report the detailed background for the discovery and development of the synthesis of homopropargylic azides by the azidoalkynylation of alkenes. Initially, a strategy involving SOMOphilic alkynes was adopted, but only resulted in a 29% yield of the desi ...

Conventional techniques for purifying macromolecular conjugates often require complex and costly installments that are inaccessible to most laboratories. In this work, we develop a one-step micropreparative method based on a trilayered polyacrylamide gel e ...

A method for optimizing at least one of a geometry, an implantation procedure, and/or stimulation protocol of one or more electrodes for an electrical stimulation of a target structure in a nervous system of a living being by a computer device, the method ...

In this paper, we study sampling from a posterior derived from a neural network. We propose a new probabilistic model consisting of adding noise at every pre- and post-activation in the network, arguing that the resulting posterior can be sampled using an ...

Given a sequence of functions

f_1,\ldots,f_n

with

f_i:\mathcal{D}\mapsto \mathbb{R}

, finite-sum minimization seeks a point

{x}^\star \in \mathcal{D}

minimizing

\sum_{j=1}^nf_j(x)/n

. In this work, we propose a key twist into the finite-sum minimizat ...

In this paper, we propose a reduced-order modeling strategy for two-way Dirichlet-Neumann parametric coupled problems solved with domain-decomposition (DD) sub-structuring methods. We split the original coupled differential problem into two sub-problems wi ...

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

Molecular quantum dynamics simulations are essential for understanding many fundamental phenomena in physics and chemistry. They often require solving the time-dependent Schrödinger equation for molecular nuclei, which is challenging even for medium-sized ...

Navigation of drones is predominantly based on sensor fusion algorithms. Most of these algorithms make use of some form of Bayesian filtering with a majority employing an Extended Kalman Filter (EKF), wherein inertial measurements are fused with a Global N ...

Driven by the need for more efficient and seamless integration of physical models and data, physics -informed neural networks (PINNs) have seen a surge of interest in recent years. However, ensuring the reliability of their convergence and accuracy remains ...

We introduce an algorithm to reconstruct a mesh from discrete samples of a shape's Signed Distance Function (SDF). A simple geometric reinterpretation of the SDF lets us formulate the problem through a point cloud, from which a surface can be extracted wit ...

This article investigates the performance and accuracy of continuous Real-Time Kinematic (RTK) Global Navigation Satellite System (GNSS) position tracking for hydromorphological surveys, based on a comprehensive river restoration monitoring campaign. The a ...

Update on yesterday's dose-Use of delivery log-files for daily adaptive proton therapy (DAPT)

Chattez avec Graph Search

Violation-aware contextual Bayesian optimization for controller performance optimization with unmodeled constraints

Adaptive projected variational quantum dynamics

Decoding electroencephalographic responses to visual stimuli compatible with electrical stimulation

SIMPLE HIERARCHICAL PLANNING WITH DIFFUSION

Mesh-based topology, shape and sizing optimization of ribbed plates

Scalable constrained optimization

A ride time-oriented scheduling algorithm for dial-a-ride problems

Modeling and optimization of PCB coils for inductive power transfer systems

SOMOphilic alkyne vs radical-polar crossover approaches: The full story of the azido-alkynylation of alkenes

Micropreparative Gel Electrophoresis for Purification of Nanoscale Bioconjugates

A method and system for optimizing design, implantation, and stimulation protocols of electrodes stimulating the nervous system

Gibbs sampling the posterior of neural networks

Efficient Continual Finite-Sum Minimization

A Reduced Order Model for Domain Decompositions with Non-conforming Interfaces

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

High-order geometric integrators for the variational Gaussian wavepacket dynamics and application to vibronic spectra at finite temperature

VDMNav: Software Architecture for Aerodynamically Constrained Navigation on Small Fixed-Wing Drones

Residual-based attention in physics-informed neural networks

Reach For the Arcs: Reconstructing Surfaces from SDFs via Tangent Points

Performance and accuracy of cross‐section tracking methods for hydromorphological habitat assessment in wadable rivers with sparse canopy conditions