Dynamically Selecting Composition Algorithms for Economical Composition as a Service

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An integer vector 𝑏 ∈ Z𝑑 is a degree sequence if there exists a hypergraph with vertices {1, … , 𝑑} such that each 𝑏𝑖 is the number of hyperedges containing 𝑖. The degree-sequence polytope 𝒵 𝑑 is the convex hull of all degree sequences. We show that all bu ...

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 ...

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 ...

Cutting plane methods are a fundamental approach for solving integer linear programs (ILPs). In each iteration of such methods, additional linear constraints (cuts) are introduced to the constraint set with the aim of excluding the previous fractional opti ...

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

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 ...

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 ...

Sample efficiency is a fundamental challenge in de novo molecular design. Ideally, molecular generative models should learn to satisfy a desired objective under minimal calls to oracles (computational property predictors). This problem becomes more apparen ...

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 ...

Probing the architecture of neuronal circuits and the principles that underlie their functional organization remains an important challenge of modern neurosciences. This holds true, in particular, for the inference of neuronal connectivity from large-scale ...

Graph neural networks (GNNs) have demonstrated promising performance across various chemistry-related tasks. However, conventional graphs only model the pairwise connectivity in molecules, failing to adequately represent higher order connections, such as m ...

Mechanical resonators are widely used in sensors, transducers and optomechanical systems, where mechanical dissipation sets the ultimate limit to performance. Over the past 15 years, the quality factors in strained mechanical resonators have increased by f ...

Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...

We prove that the Cohn-Elkies linear programming bound for sphere packing is not sharp in dimension 6. The proof uses duality and optimization over a space of modular forms, generalizing a construction of Cohn- Triantafillou [Math. Comp. 91 (2021), pp. 491 ...

We develop a very general version of the hyperbola method which extends the known method by Blomer and Brudern for products of projective spaces to complete smooth split toric varieties. We use it to count Campana points of bounded log-anticanonical height ...

At room temperature, mechanical motion driven by the quantum backaction of light has been observed only in pioneering experiments in which an optical restoring force controls the oscillator stiffness1,2. For solid-state mechanical resonators in which oscil ...

The COVID-19 pandemic has led to a significant increase in working from home worldwide, making the workfrom-home (WFH) setting a crucial context for studying the influence of indoor environmental quality (IEQ) on workers' well-being and productivity. A nar ...

This directory contains open-source data obtained using a single-bladed H-type vertical-axis wind turbine prototype with individual blade pitching. This data results from the optimisation of the blade's pitching kinematics using a genetic algorithm at two ...

An integer linear program is a problem of the form max{c^T x : Ax=b, x >= 0, x integer}, where A is in Z^(n x m), b in Z^m, and c in Z^n. Solving an integer linear program is NP-hard in general, but there are several assumptions for which it becomes fixed ...

The field of biometrics, and especially face recognition, has seen a wide-spread adoption the last few years, from access control on personal devices such as phones and laptops, to automated border controls such as in airports. The stakes are increasingly ...

Dynamically Selecting Composition Algorithms for Economical Composition as a Service

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Integer points in the degree-sequence polytope

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

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

Learning to Remove Cuts in Integer Linear Programming

Extensions of Peer Prediction Incentive Mechanisms

Gibbs sampling the posterior of neural networks

Adaptive projected variational quantum dynamics

Augmented Memory: Sample-Efficient Generative Molecular Design with Reinforcement Learning

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

Ensemble learning and ground-truth validation of synaptic connectivity inferred from spike trains

Molecular hypergraph neural networks

Ultrahigh-quality-factor micro- and nanomechanical resonators using dissipation dilution

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Six-dimensional sphere packing and linear programming

HYPERBOLA METHOD ON TORIC VARIETIES

Room-temperature quantum optomechanics using an ultralow noise cavity

A state-of-the-art, systematic review of indoor environmental quality studies in work-from-home settings

Data from: Optimal blade pitch control for enhanced vertical-axis wind turbine performance

Results on Sparse Integer Programming and Geometric Independent Sets

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms