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] . Diving Deep into Sentiment: Understanding Fine-tuned CNNs for Visual Sentiment Prediction. In 1st International Workshop on Affect and Sentiment in Multimedia. Brisbane, Australia: ACM; 2015. 
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(506.22 KB). Layer-wise CNN Surgery for Visual Sentiment Prediction. . 2015. (1.51 MB)
(1.51 MB). Clustering and Prediction of Adjective-Noun Pairs for Affective Computing. . 2016. (10.38 MB)
(10.38 MB). Is a “happy dog” more “happy” than “dog”? - Adjective and Noun Contributions for Adjective-Noun Pair prediction. NIPS Women in Machine Learning Workshop. Barcelona; 2016. (3.11 MB)
(3.11 MB). From Pixels to Sentiment: Fine-tuning CNNs for Visual Sentiment Prediction. Image and Vision Computing. 2017;. (1.92 MB)
(1.92 MB). Learning to Skip State Updates in Recurrent Neural Networks. . 2017. (961.49 KB)
(961.49 KB). More cat than cute? Interpretable Prediction of Adjective-Noun Pairs. In ACM Multimedia 2017 Workshop on Multimodal Understanding of Social, Affective and Subjective Attributes. Mountain View, CA (USA): ACM SIGMM; 2017. (9.62 MB)
(9.62 MB). Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks. In NIPS Time Series Workshop 2017. Long Beach, CA, USA; 2017. (427.72 KB)
(427.72 KB). Sentiment concept embedding for visual affect recognition. In Multimodal Behavior Analysis in theWild. 1st ed. Elsevier; 2018.
. Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks. In International Conference on Learning Representations (ICLR). 2018.