CybAI news

arXiv:2408.03388v1 Announce Type: new Abstract: The gamma belief network (GBN), often regarded as a deep topic model, has demonstrated its potential for uncovering multi-layer interpretable latent representations in text data. Its notable capability to acquire interpretable latent factors is partially attributed to sparse and non-negative gamma-distributed latent variables. However, the existing GBN and its variations are constrained by the linear generative model, thereby limiting their expressiveness and applicability. To address this limitation, we introduce the generalized gamma belief network (Generalized GBN) in this paper, which extends the original linear generative model to a more expressive non-linear generative model. Since the…

[Submitted on 6 Aug 2024] View a PDF of the paper titled Set2Seq Transformer: Learning Permutation Aware Set Representations of Artistic Sequences, by Athanasios Efthymiou and 3 other authors View PDF Abstract:We propose Set2Seq Transformer, a novel sequential multiple instance architecture, that learns to rank permutation aware set representations of sequences. First, we illustrate that learning temporal position-aware representations of discrete timesteps can greatly improve static visual multiple instance learning methods that do not regard temporality and concentrate almost exclusively on visual content analysis. We further demonstrate the significant advantages of end-to-end sequential multiple instance learning, integrating visual content and…

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Source link lol

Generative AI has the potential to change business operations across a vast range of sectors. In terms of securing business growth, the GenAI revolution cannot be understated.  With projections suggesting that the global generative AI market size is set to reach $967.65 billion by 2032, representing a CAGR of 39.6%, it's clear that the artificial intelligence boom will be a major disruptive force throughout business operations worldwide.  In addition to this, McKinsey data suggests that the impact of generative AI on productivity has the potential to add trillions of dollars to the global economy. For businesses eager to scale up their operations…