Top 10 tri.global Competitors

tyndall.ie

Explore Tyndall's pioneering research at the intersection of ICT, Medtech, and Pharma. Learn about our advancements in electronics, photonics, AI, and systems integration for healthcare innovation.

cerfacs.fr

Date de dernière modification de ce document ( Politique de confidentialité de l’Extranet Cerfacs ) : 29 Septembre 2025 Présentation du CERFACS Le Cerfacs est un centre de recherche fondamentale et appliquée, spécialisé dans la modélisation et la simulation numérique. Par ses moyens et savoir-faire en calcul haute performance, le Cerfacs traite des grands problèmes […]

ncsa.illinois.edu

The National Center for Supercomputing Applications is a leader in advanced computing, software, data, networking, and visualization resources.

icsi.berkeley.edu

Government grants, philanthropic support, and corporate partnerships fuel our research and expand our impact.

simula.no

Current job openings at Simula

atr.jp

社会課題と向き合う科学技術の最前線

naverlabs.com

네이버랩스는 한국과 유럽의 우수한 연구자들이 함께 AI, 로보틱스, 자율주행, 3D/HD 매핑, AR 등의 연구에 매진하고 있습니다. 가장 독창적이며 앞선 기술력을 통해 사람, 머신, 공간, 정보를 새롭게 연결할 네이버 플랫폼의 미래를 준비하는 것이 우리의 미션입니다.

ieeevr.org

The 32nd IEEE Conference on Virtual Reality and 3D User Interfaces

arxiv.org

A system of non-tradable credits that flow between individuals like karma, hence proposed under that name, is a mechanism for repeated resource allocation that comes with attractive efficiency and fairness properties, in theory. In this study, we test karma in an online experiment in which human subjects repeatedly compete for a resource with time-varying and stochastic individual preferences or urgency to acquire the resource. We confirm that karma has significant and sustained welfare benefits even in a population with no prior training. We identify mechanism usage in contexts with sporadic high urgency, more so than with frequent moderate urgency, and implemented as a simple (binary) karma bidding scheme as particularly effective for welfare improvements: relatively larger aggregate efficiency gains are realized that are (almost) Pareto superior. These findings provide guidance for further testing and for future implementation plans of such mechanisms in the real world.