Essays about: "Disentanglement"
Showing result 1 - 5 of 7 essays containing the word Disentanglement.
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1. Unlocking the True Value of Intellectual Capital: A Study of the Valuation Relevance of Intellectual Capital in an M&A Intensive Era
University essay from Handelshögskolan i Stockholm/Institutionen för redovisning och finansieringAbstract : Capital market actors must understand the fundamental value-drivers in society, yet accounting standards face difficulties in capturing Intellectual Capital (IC) information. Meanwhile, the number of acquisitions is ever-growing, but research on the valuation relevance of IC in mergers and acquisitions (M&A) is lacking. READ MORE
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2. Board Gender Diversity and Firm Financial Performance: The Role of Innovation
University essay from Handelshögskolan i Stockholm/Institutionen för redovisning och finansieringAbstract : This quantitative study investigates the inter-relationship between board gender diversity, innovation, and subsequent firm financial performance. We use two multivariate OLS regression models on an unbalanced panel dataset with firm-year observations for listed companies headquartered in the U.S. between 2012-2019. READ MORE
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3. Towards Latent Space Disentanglement of Variational AutoEncoders for Language
University essay from Uppsala universitet/Institutionen för lingvistik och filologiAbstract : Variational autoencoders (VAEs) are a neural network architecture broadly used in image generation (Doersch 2016). VAEs are neural network models that encode data from some domain and project it into a latent space (Doersch 2016). READ MORE
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4. 3D Facial Modelling for Valence Estimation
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : We, as humans, purposely alter our facial expression to convey information during our daily interactions. However, our facial expressions can also unconsciously change based on external stimuli. READ MORE
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5. Analysis of the effect of latent dimensions on disentanglement in Variational Autoencoders
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Disentanglement is a subcategory to Representaton learning where we, apart from believing that useful properties can be extracted from the data in a more compact form, also envision that the data itself is constituted from a lower-dimensional subset of explanatory factors. Explanatory factors are an ambiguous concept and what they portray varies with the dataset. READ MORE