ICCBR is heading to RGU in Aberdeen, Scotland this year. Find more information on the conference webpage (https://t.co/fTJLRGo1aZ) and take a note of the upcoming submission dates (https://t.co/BlyPHAff9M)
@labo_Loria We're looking forward to returning to @ComputingRGU next July for the 31st International Conference on CBR. Next year's PC chairs will be @stmassie and Sutanu Chakraborti.
Au revoir Nancy! Thanks to the team @labo_Loria for hosting #ICCBR2022 and to all the chairs, speakers and participants for making the conference a success. This year's proceedings are available at SpringerLink: https://t.co/Ua1nKyavEW
#ICCBR2022 Best Paper Award 👏: @EoinDelaney_, @derekgreene Laurence Shalloo, Michael Lynch and @keanema for their paper
Forecasting for Sustainable Dairy Produce: Enhanced Long-Term, Milk-Supply Forecasting Using k-NN for Data Augmentation, with Prefactual Explanations for XAI
Very proud of my Ph.D. students Betül Bayrak & Paola Veites for their 3rd place in the #iccbr2022#XCBR challenge organized by the
@isee4xai project. In the picture with us is David Leake from the winning
@IULuddy team - congrats!
#AI experts answer your questions!
In the fourth installment of our AMA video series we are talking to Dr. David Leake, Professor of Computer Science at Indiana University. This week's video tackles topics like building artificial wisdom, concerns & excitements in the AI world.
The CfP for the ICCBR'22 DC is open and we'll be organising a 1-hr webinar for potential participants on June 13. For more information, please visit: https://t.co/ykf2raryWi
Day 2 at ICCBR 2021 coming up with a keynote by @santiontanon and two main conference sessions
on Explainable AI and Adaptation. For more, check out https://t.co/2SQrrQqjbf
Very pleased to be talking this PM in Spain (unfortunately virtually)on our work on #XAI@keanema at the Explainable Case Based Reasoning (XCBR) workshop as part of @CBRConf#iccbr21#xcbr
📄An interesting and informative presentation on Mapping the challenges and opportunities of CBR for #eXplainable#AI by Belén Díaz Agudo, Professor at @unicomplutense, during the 27th #ICCBR`19.
Take a look👉https://t.co/fqbrQB4lO5
@belendFdI@CBRConf @sierra_carles
Thanks to @CBRConf for accepting our paper "How Case-Based Reasoning Explains Neural Networks: A Theoretical Analysis of XAI Using Post-Hoc Explanation- by-Example from a Survey of ANN-CBR Twin-Systems" #ICCBR#XAI#DeepLearning#MachineLearning#CBR https://t.co/HyVbIkDyVV pre-p
Durante la (#ICCBR) celebrada en Alemania, tuve la oportunidad de asistir a diferentes e interesantes ponencias relacionadas con la temática de
@CBRConf, Explainable #AI (XAI). Entre ellas puedo resaltar una excelente intervención de @DanMagazzeni.
https://t.co/rInMxtzeP0