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Decentralized Collective World Model for Emergent Communication and Coordination

Decentralized Collective World Model for Emergent Communication and Coordination

4 April 2025
Kentaro Nomura
Tatsuya Aoki
Tadahiro Taniguchi
Takato Horii
ArXiv (abs)PDFHTML

Papers citing "Decentralized Collective World Model for Emergent Communication and Coordination"

13 / 13 papers shown
Title
Reality Check: A New Evaluation Ecosystem Is Necessary to Understand AI's Real World Effects
Reality Check: A New Evaluation Ecosystem Is Necessary to Understand AI's Real World Effects
Reva Schwartz
Rumman Chowdhury
Akash Kundu
Heather Frase
Marzieh Fadaee
...
Andrew Thompson
Maya Carlyle
Qinghua Lu
Matthew Holmes
Theodora Skeadas
47
0
0
24 May 2025
Uncertainty-aware Bayesian machine learning modelling of land cover classification
Uncertainty-aware Bayesian machine learning modelling of land cover classification
Samuel Bilson
Anna Pustogvar
UQCV
145
1
0
27 Mar 2025
Analysis and Comparison of Classification Metrics
Analysis and Comparison of Classification Metrics
Luciana Ferrer
56
20
0
12 Sep 2022
Robustness of convolutional neural networks to physiological ECG noise
Robustness of convolutional neural networks to physiological ECG noise
Jenny Venton
P. Harris
A. Sundar
N. Smith
P. Aston
50
26
0
02 Aug 2021
Aleatoric uncertainty for Errors-in-Variables models in deep regression
Aleatoric uncertainty for Errors-in-Variables models in deep regression
J. Martin
Clemens Elster
UQCVUDBDL
57
9
0
19 May 2021
Continental-scale land cover mapping at 10 m resolution over Europe
  (ELC10)
Continental-scale land cover mapping at 10 m resolution over Europe (ELC10)
Z. Venter
M. Sydenham
64
68
0
22 Apr 2021
Hands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Users
Hands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Users
Laurent Valentin Jospin
Wray Buntine
F. Boussaïd
Hamid Laga
Bennamoun
OODBDLUQCV
84
628
0
14 Jul 2020
Uncertainty Quantification for Bayesian Optimization
Uncertainty Quantification for Bayesian Optimization
Rui Tuo
Wei Cao
UQCV
26
5
0
04 Feb 2020
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction
  to Concepts and Methods
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods
Eyke Hüllermeier
Willem Waegeman
PERUD
244
1,415
0
21 Oct 2019
Bag of Tricks for Image Classification with Convolutional Neural
  Networks
Bag of Tricks for Image Classification with Convolutional Neural Networks
Tong He
Zhi-Li Zhang
Hang Zhang
Zhongyue Zhang
Junyuan Xie
Mu Li
284
1,419
0
04 Dec 2018
What Uncertainties Do We Need in Bayesian Deep Learning for Computer
  Vision?
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?
Alex Kendall
Y. Gal
BDLOODUDUQCVPER
354
4,709
0
15 Mar 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCVBDL
827
9,318
0
06 Jun 2015
Practical Bayesian Optimization of Machine Learning Algorithms
Practical Bayesian Optimization of Machine Learning Algorithms
Jasper Snoek
Hugo Larochelle
Ryan P. Adams
359
7,942
0
13 Jun 2012
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