Generative urban design: A systematic review on problem formulation, design generation, and decision-making
Urban design is the process of designing and shaping the physical forms of cities, towns,
and suburbs. It involves the arrangement and design of street systems, groups of buildings …
and suburbs. It involves the arrangement and design of street systems, groups of buildings …
ProcessGAN: Supporting the creation of business process improvement ideas through generative machine learning
Business processes are a key driver of organizational success, which is why business
process improvement (BPI) is a central activity of business process management. Despite an …
process improvement (BPI) is a central activity of business process management. Despite an …
Active Divergence with Generative Deep Learning--A Survey and Taxonomy
Generative deep learning systems offer powerful tools for artefact generation, given their
ability to model distributions of data and generate high-fidelity results. In the context of …
ability to model distributions of data and generate high-fidelity results. In the context of …
Generative deep learning in architectural design
D Newton - Technology| Architecture+ Design, 2019 - Taylor & Francis
Generative Adversarial Networks (GANs) are an emerging research area in deep learning
that have demonstrated impressive abilities to synthesize designs, however, their …
that have demonstrated impressive abilities to synthesize designs, however, their …
Novelty detection with gan
M Kliger, S Fleishman - arXiv preprint arXiv:1802.10560, 2018 - arxiv.org
The ability of a classifier to recognize unknown inputs is important for many classification-
based systems. We discuss the problem of simultaneous classification and novelty …
based systems. We discuss the problem of simultaneous classification and novelty …
Novelty generation framework for AI agents in angry birds style physics games
Handling novel situations is a critical capability of Artificial Intelligence (AI) agents when
working in open-world physical environments. To develop and evaluate these agents, we …
working in open-world physical environments. To develop and evaluate these agents, we …
Self-improving generative artificial neural network for pseudorehearsal incremental class learning
Deep learning models are part of the family of artificial neural networks and, as such, they
suffer catastrophic interference when learning sequentially. In addition, the greater number …
suffer catastrophic interference when learning sequentially. In addition, the greater number …
Systemic oversimplification limits the potential for human-AI partnership
JS Metcalfe, BS Perelman, DL Boothe… - IEEE Access, 2021 - ieeexplore.ieee.org
The modern world is evolving rapidly, especially with respect to the development and
proliferation of increasingly intelligent, artificial intelligence (AI) and AI-related technologies …
proliferation of increasingly intelligent, artificial intelligence (AI) and AI-related technologies …
GAN‐C: A generative adversarial network with a classifier for effective event prediction
Event prediction is essential in social network (SN) analysis to study the SN's evolutionary
patterns (communities). Machine learning (ML) models are often used to predict events in …
patterns (communities). Machine learning (ML) models are often used to predict events in …
Toward a neuro-inspired creative decoder
Creativity, a process that generates novel and meaningful ideas, involves increased
association between task-positive (control) and task-negative (default) networks in the …
association between task-positive (control) and task-negative (default) networks in the …