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The Power of Generative AI: A Review of Requirements, Models, Input–Output Formats, Evaluation Metrics, and Challenges

open access: yesFuture 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
doaj   +3 more sources

Optical generative models. [PDF]

open access: yesNature
Abstract 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

Do generative models learn rare generative factors? [PDF]

open access: yesFrontiers in Artificial Intelligence
Generative 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
doaj   +2 more sources

Generative AI models for different steps in architectural design: A literature review

open access: yesFrontiers of Architectural Research
Recent 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
doaj   +3 more sources

Lifelong generative modeling [PDF]

open access: yesNeurocomputing, 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
openaire   +5 more sources

Improving students' high-level mathematical thinking skills through generative learning models

open access: yesInternational 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
doaj   +1 more source

Generative modeling of turbulence

open access: yesPhysics 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
openaire   +3 more sources

The generic model of general relativity [PDF]

open access: yesArabian Journal of Mathematics, 2019
55 pages, no ...
Tsamparlis, M., Paliathanasis, A.
openaire   +4 more sources

Generative Models for Active Vision

open access: yesFrontiers 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
doaj   +1 more source

Generative Models of Brain Dynamics

open access: yesFrontiers in Artificial Intelligence, 2022
This review article gives a high-level overview of the approaches across different scales of organization and levels of abstraction. The studies covered in this paper include fundamental models in computational neuroscience, nonlinear dynamics, data ...
Mahta Ramezanian-Panahi   +12 more
doaj   +1 more source

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