Bjarke Felbo
TitelZitiert vonJahr
Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm
B Felbo, A Mislove, A Søgaard, I Rahwan, S Lehmann
arXiv preprint arXiv:1708.00524, 2017
Using deep learning to predict demographics from mobile phone metadata
B Felbo, P Sundsøy, S Lehmann, YA de Montjoye
Closing the AI Knowledge Gap
Z Epstein, BH Payne, JH Shen, A Dubey, B Felbo, M Groh, N Obradovich, ...
arXiv preprint arXiv:1803.07233, 2018
Modeling the Temporal Nature of Human Behavior for Demographics Prediction
B Felbo, P Sundsøy, S Lehmann, YA de Montjoye
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2017
Evaluating Style Transfer for Text
R Mir, B Felbo, N Obradovich, I Rahwan
arXiv preprint arXiv:1904.02295, 2019
Comparing Models of Associative Meaning: An Empirical Investigation of Reference in Simple Language Games
JH Shen, M Hofer, B Felbo, R Levy
arXiv preprint arXiv:1810.03717, 2018
Teaching machines about emotions
B Felbo
Massachusetts Institute of Technology, 2018
TuringBox: An Experimental Platform for the Evaluation of AI Systems.
Z Epstein, BH Payne, JH Shen, CJ Hong, B Felbo, A Dubey, M Groh, ...
IJCAI, 5826-5828, 2018
A First Step in Combining Cognitive Event Features and Natural Language Representations to Predict Emotions
A Campero, B Felbo, JB Tenenbaum, R Saxe
arXiv preprint arXiv:1710.08048, 2017
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