Top Tweets for #Kandinskypatterns
Awesome paper by the team of @kerstingAIML @TUDarmstadt @Hessian_AI on #KandinskyPatterns important work for #artificialintelligence #ai generally and #humancenteredai #hcai specifically and an important read for the #machinelearning community
https://t.co/YLJgKRZnRS
Great that @MIT_CSAIL is taking up the idea of our #Kandinskypatterns see: https://t.co/SbmZKLoYHR - this is important for our #XAI #AI #explainableAI #HCAI #HumanCenteredAI community and an important step for #machinelearning https://t.co/BpnHyvyZym
The Oct issue of #IEEE Spectrum is worth reading: "Why is #AI so dumb?" as @pabbeel pointed out in his keynote at CVPR: the challenge of the next 7 years is to bring #intelligence to #robotics - so it's all about #HumanCenteredAI and also a case for #KANDINSKYPatterns :-)
Next speaker at #EMPAIAAcademy is Andreas Holzinger (@aholzin), Inst. for Medical Informatics, Statistics and Documentation of @MedUniGraz, on: “Current trends in AI in pathology” | #human-in-the-loop #HumanCenteredAI #ExplainableAI #xai #KANDINSKYPatterns
We are seeking feedback on our #KANDINSKYPatterns experimental exploration environment for #Patternanalysis and #Machineintelligence from the international research community in #ai #machinelearning and #explainableai #xAI https://t.co/9m47hV0hpw
oops ... on 9/14 I made our 3-mins #research statement of our #HumanCenteredAI group on #explainableai #xai #causability and #Kandinskypatterns for #ai and #machinelearning in #medicalai but forgot to make it public ... mea culpa ... here finally it is
https://t.co/Fxu5ZC0P4X
Project partner Prof. Andreas Holzinger @aholzin from #MedicalUniversityGraz proudly presents the hot-off-the-press edition of Springer/Nature LNAI 12090. #ai and #machinelearning for #digitalpathology are a major part of #FeatureCloud. #KandinskyPatterns in the background 😉...
thanks to my fellow editor colleagues and to great authors, I am holding the hot off the press edition of Springer/Nature LNAI 12090 #ai #machinelearning for #digitalpathology in my hands ... #KandinskyPatterns of course in the background ... https://t.co/mPZEGG89Al
#kandinskypatterns our #xai playground for #explainableai research as guest in the Tübingen center for #ai and #machinelearning https://t.co/r2x6J4ddxP
#Kandinskypatterns as an exploration environment for testing #xai and experimenting with #explainableai which will be very important for #machinelearning in future #ai systems https://t.co/uHZH8N4NMJ
@Ann_Qnn Anna Saranti presented in her #ai talk on #explainableai #xai the #KandinskyPatterns at @WeAreDevs the World's Largest #Developers Congress to the #machinelearning community in Vienna https://t.co/nqsrHfQKSg
@sunsiren Charlotte Han interested in #ai #humanai and particularly in #humancenteredai just visited the #humancenteredai group in Graz, Austria and was enthusiastic about the #KANDINSKYpatterns our "Swiss-Knife" for #explainableai #xai and #machinelearni…https://t.co/7IG2u02n6m
For a brief non-expert intro to the #kandinskypatterns - our swiss-knife for the study of #explainableai - watch the TEDx talk, organized by a great team in lovely #Graz, Austria; we will provide deeper technical insights to the #p…https://t.co/A3Bx8w6CdS https://t.co/g4jyWNSWSY
Successfully started our FWF basic research project #explainableai setting up and enlarging our group. We will make all outcomes of this project available to the international #ai #machinelearning community; the #kandinskypatterns…https://t.co/AXAPHuGEIn https://t.co/Sm1Y94b5kI
Awesome and highly relevant work for #deeplearning however, the main issue in real-world data is the evaluation of #ai #machinelearning #algorithms against a ground truth,
which was a motivation for developing the #KandinskyPattern…https://t.co/Qdg54IxIrl https://t.co/Tu8cDuicMu
A good article on #machinelearning #ai in #medicine and #healthinformatics emphasizing the importance of ground truth, hence a very good motivation
for the importance of our Swiss knife the #KandinskyPatterns for #explainableai https://t.co/qhFbAVC1hb
I am so grateful to Google #ai for this post: If I tell my students, they do'nt believe me, now I can say Google has said it! Ground-truth for #machinelearning was exactly the motivation for our #KandinskyPatterns which can be seen as a swiss-knife for the study of #explainableai
Since generative models have no “ground-truth,” evaluating their performance can be difficult. New quantitative metrics use the Fréchet distance between model and source distributions to evaluate the quality of generative audio and video. Learn more below. https://t.co/oI5lMx4bVG
Happy to announce that our #KandinskyPatterns #challenge for #explainableAI has been accepted at the CiML-session at the #NeurIPS #machinelearning conference in Vancouver; find all information on Github, see https://t.co/AmsNjPHxna
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