Algorithme d'Euclide

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

Nikolaos Geroliminis, Claudia Bongiovanni, Mor Kaspi

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 ...

Pergamon-Elsevier Science Ltd2024

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

Yingying Ren

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 ...

Association for Computing Machinery2024

Adaptive projected variational quantum dynamics

Giuseppe Carleo, David Linteau, Stefano Barison

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 ...

Amer Physical Soc2024

Gibbs sampling the posterior of neural networks

Lenka Zdeborová, Emanuele Troiani, Giovanni Piccioli

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 ...

Iop Publishing Ltd2024

Molecular hypergraph neural networks

Philippe Schwaller, Junwu Chen

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 ...

Aip Publishing2024

Robust Collaborative Learning with Linear Gradient Overhead

Rachid Guerraoui, John Stephan, Sadegh Farhadkhani, Le Nguyen Hoang, Nirupam Gupta, Rafaël Benjamin Pinot

Collaborative learning algorithms, such as distributed SGD (or D-SGD), are prone to faulty machines that may deviate from their prescribed algorithm because of software or hardware bugs, poisoned data or malicious behaviors. While many solutions have been ...

PLMR2023

Phenomenological theory of variational quantum ground-state preparation

Ivano Tavernelli, Giuseppe Carleo

The variational approach is a cornerstone of computational physics, considering both conventional and quantum computing computational platforms. The variational quantum eigensolver algorithm aims to prepare the ground state of a Hamiltonian exploiting para ...

Amer Physical Soc2023

Equivalence Checking for Orthocomplemented Bisemilattices in Log-Linear Time

Viktor Kuncak, Simon Guilloud

We present a quasilinear time algorithm to decide the word problem on a natural algebraic structures we call orthocomplemented bisemilattices, a subtheory of boolean algebra. We use as a base a variation of Hopcroft, Ullman and Aho algorithm for tree isomo ...

Springer2022

On the Efficiency of Polar-Like Decoding for Symmetric Codes

Rüdiger Urbanke, Kirill Ivanov

The recently introduced polar codes constitute a breakthrough in coding theory due to their capacity-achieving property. This goes hand in hand with a quasilinear construction, encoding, and successive cancellation list decoding procedures based on the Plo ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Algorithme d'Euclide

Graph Chatbot

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

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

Adaptive projected variational quantum dynamics

Gibbs sampling the posterior of neural networks

Molecular hypergraph neural networks

Robust Collaborative Learning with Linear Gradient Overhead

Phenomenological theory of variational quantum ground-state preparation

Equivalence Checking for Orthocomplemented Bisemilattices in Log-Linear Time

Generalised Implicit Neural Representations

On the Efficiency of Polar-Like Decoding for Symmetric Codes

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

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

Adaptive projected variational quantum dynamics

Gibbs sampling the posterior of neural networks

Molecular hypergraph neural networks

Robust Collaborative Learning with Linear Gradient Overhead

Phenomenological theory of variational quantum ground-state preparation

On the Efficiency of Polar-Like Decoding for Symmetric Codes

Generalised Implicit Neural Representations

Equivalence Checking for Orthocomplemented Bisemilattices in Log-Linear Time