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Future Internet, 2023 Generative artificial intelligence (AI) has emerged as a powerful technology with numerous applications in various domains. There is a need to identify the requirements and evaluation metrics for generative AI models designed for specific tasks.
Ajay Bandi +2 more
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Do generative models learn rare generative factors? [PDF]
Frontiers in Artificial IntelligenceGenerative models are becoming a promising tool in AI alongside discriminative learning. Several models have been proposed to learn in an unsupervised fashion the corresponding generative factors, namely the latent variables critical for capturing the ...
Fasih Haider +3 more
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Optical generative models. [PDF]
NatureAbstract Generative models cover various application areas, including image and video synthesis, natural language processing and molecular design, among many others1–11. As digital generative models become larger, scalable inference in a fast and energy-efficient manner becomes a challenge12–14.
Chen S, Li Y, Wang Y, Chen H, Ozcan A.
europepmc +6 more sources
Generative AI models for different steps in architectural design: A literature review
Frontiers of Architectural ResearchRecent advances in generative artificial intelligence (AI) technologies have been significantly driven by models such as generative adversarial networks (GANs), variational autoencoders (VAEs), and denoising diffusion probabilistic models (DDPMs ...
Chengyuan Li +4 more
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Lifelong generative modeling [PDF]
Neurocomputing, 2020 Lifelong learning is the problem of learning multiple consecutive tasks in a sequential manner, where knowledge gained from previous tasks is retained and used to aid future learning over the lifetime of the learner. It is essential towards the development of intelligent machines that can adapt to their surroundings. In this work we focus on a lifelong
Jason Ramapuram +2 more
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Improving students' high-level mathematical thinking skills through generative learning models
International Journal of Trends in Mathematics Education Research, 2023 The purpose of this study was to (1) analyze the achievement of high-level mathematical thinking skills of students who received learning with generative models and learning with conventional models, (2) analyze the increase in students' high-level ...
La Moma, Hanisa Tamalene
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Generative modeling of turbulence
Physics of Fluids, 2022 We present a mathematically well-founded approach for the synthetic modeling of turbulent flows using generative adversarial networks (GAN). Based on the analysis of chaotic, deterministic systems in terms of ergodicity, we outline a mathematical proof that GAN can actually learn to sample state snapshots from the invariant measure of the chaotic ...
C. Drygala +3 more
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The generic model of general relativity [PDF]
Arabian Journal of Mathematics, 2019 55 pages, no ...
Tsamparlis, M., Paliathanasis, A.
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Generative Models for Active Vision
Frontiers in Neurorobotics, 2021 The active visual system comprises the visual cortices, cerebral attention networks, and oculomotor system. While fascinating in its own right, it is also an important model for sensorimotor networks in general.
Thomas Parr +5 more
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CoRR, 2021 Generative modeling has recently seen many exciting developments with the advent of deep generative architectures such as Variational Auto-Encoders (VAE) or Generative Adversarial Networks (GAN). The ability to draw synthetic i.i.d. observations with the same joint probability distribution as a given dataset has a wide range of applications including ...
Johan Leduc, Nicolas Grislain
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