Generative spatial artificial intelligence for sustainable smart cities: A pioneering large flow model for urban digital twin

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Context. Technical and social innovations are central to the transition to renewable energy systems. Despite the availability of innovative technologies for renewable energy production, management, and e-mobility, their widespread societal adoption remains ...

For decades, mega-events have been employed as catalysts for urban development, transforming cityscapes, and generating socioeconomic growth. More recently, however, there has been a renewed focus on repurposing industrial heritage sites for hosting mega-e ...

As medical datasets rapidly expand, creating detailed annotations of different body structures becomes increasingly expensive and time-consuming. We consider that requesting radiologists to create detailed annotations is unnecessarily burdensome and that p ...

Current trends in artificial intelligence toward larger models demand a rethinking of both hardware and algorithms. Photonics-based systems offer high-speed, energy-efficient computing units, provided algorithms are designed to exploit photonics' unique st ...

The application of machine learning in medicine and healthcare has led to the creation of numerous diagnostic and prognostic models. However, despite their success, current approaches generally issue predictions using data from a single modality. This stan ...

Deep neural networks often fail to generalize when deployed in dynamic and unpredictable real-world environments, where data distributions at test time can differ significantly from those encountered during training. Since simulating all possible distribut ...

In the face of growing societal, public health and environmental challenges linked to the functioning of the biosphere, strong evolutionary literacy emerges as indispensable to plan and achieve sustainable futures. However, research on evolution education ...

This paper employs a comparative analysis to investigate the state-led use of industrial heritage in major Chinese mega-events, delving into the three cases of the Guangzhou Asian Games, the Shanghai Expo, and the Beijing Winter Olympics. Examining the evo ...

The advent of the "generative age"marks a pivotal moment in AI evolution, with models like OpenAI's GPT-4 and DALL-E transforming content creation across various fields. These advancements bring unprecedented efficiency and new applications but also presen ...

Sign language is vital for communication within the deaf and hard-of-hearing community. Avatar-based methods and deep learning techniques like Generative Adversarial Networks have shown promise in generating sign language video content. One of the challeng ...

Sharpness-aware minimization (SAM) has been shown to improve the generalization of neural networks. However, each SAM update requires sequentially computing two gradients, effectively doubling the per-iteration cost compared to base optimizers like SGD. We ...

Generative spatial artificial intelligence for sustainable smart cities: A pioneering large flow model for urban digital twin

Chattez avec Graph Search

Spaces of Interface: Proximity in the Diffusion of Energy Innovations

Revitalizing Industrial Heritage: Mega-events and collective memory in public space transformation

Label Critic: Design Data Before Models

Resource-efficient photonic networks for next-generation AI computing

Automated Ensemble Multimodal Machine Learning for Healthcare

Adaptive Test-Time Learning Under Domain Shift: From Augmentation to Prolonged Adaptation

Evolutionary literacy as a catalyst for sustainable futures: connecting biological evolution education and education for sustainability

The state-led approach to industrial heritage in China's mega-events: capital accumulation, urban regeneration, and heritage preservation

Déjà Vu: Uncanny and Serendipitous Re-encountering of Audiovisual Archives

Content-Based Objective Evaluation of Artificially Generated Sign Language Videos

SAMPa: Sharpness-aware Minimization Parallelized