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As artificial intelligence (AI) becomes increasingly integrated into various aspects of daily life, the need for AI literacy continues to grow. Accordingly, both educators and students must develop a critical understanding of AI systems and acquire the ski ...

Learning manipulation from demonstration is a key way for humans to teach complex tasks. However, this domain mainly focuses on kinetic teaching, and does not consider imitation of interaction forces which is essential for more contact rich tasks. We propo ...

Two design studios were successively taught in two schools of architecture: one at the Harvard Graduate School of Design (GSD) and the other at the Swiss Federal Institute of Technology in Lausanne (EPFL) in Lausanne, Switzerland, based on "A Global Morato ...

Graph-based representation approaches have been proven to be successful in the analysis of biomedical data due to their capability of capturing intricate dependencies between biological entities, such as the spatial organization of different cell types in ...

Nonlinearity of dynamic systems plays a key role in neuromorphic computing, which is expected to reduce the ever-increasing power consumption of machine learning and artificial intelligence applications. For spin waves (magnons), nonlinearity combined with ...

PolyGloT, a novel framework for educators and students, is designed to create, curate, and engage in personalized learning paths in digital education. This open, adaptable, and versatile framework facilitates the design and consumption of adaptive learning ...

Innovations in wearable technology and artificial intelligence have enabled consumer devices to process and transmit data about human mental states (cognitive, affective, and conative) through what this paper refers to as "cognitive biometrics."Devices suc ...

In recent years, the rapid advancement of artificial intelligence (AI) technologies has significantly impacted various sectors, including public governance at the local level. However, there exists a limited understanding of the overarching narrative surro ...

In the context of smart cities, ensuring road safety is crucial due to increasing urbanization and the interconnected nature of contemporary urban environments. Leveraging innovative technologies is essential to mitigate risks and create safer communities. ...

Objective. Vision restoration approaches, such as prosthetics and optogenetics, provide visual perception to blind individuals in clinical settings. Yet their effectiveness in daily life remains a challenge. Stereotyped quantitative tests used in clinical ...

The increasing implementation of programs supported by machine learning in medical contexts will affect psychiatry. It is crucial to accompany this development with careful ethical considerations informed by empirical research involving experts from the fi ...

While road obstacle detection techniques have become increasingly effective, they typically ignore the fact that, in practice, the apparent size of the obstacles decreases as their distance to the vehicle increases. In this letter, we account for this by c ...

Abstractive summarization has seen big improvements in recent years, mostly due to advances in neural language modeling, language model pretraining, and scaling models and datasets. While large language models generate summaries that are fluent, coherent, ...

The use of machine learning for predicting ecotoxicological outcomes is promising, but underutilized. The curation of data with informative features requires both expertise in machine learning as well as a strong biological and ecotoxicological background, ...

Recent developments in soft actuation demand for resilient, responsive materials with locally varying compositions that are sufficiently stiff to exhibit significant actuation forces. Hydrogels are inherently responsive to certain stimuli. Yet, they typica ...

The prospect of massive parallelism of optics enabling fast and low energy cost operations is attracting interest for novel photonic circuits where 3-dimensional (3D) implementations have a high potential for scalability. Since the technology for data inpu ...

Information is the resolution of uncertainty and manifests itself as patterns. Although complex, most observable phenomena are not random and instead are associated with deterministic, chaotic systems. The underlying patterns and symmetries expressed from ...

We present a discriminative clustering approach in which the feature representation can be learned from data and moreover leverage labeled data. Representation learning can give a similarity-based clustering method the ability to automatically adapt to an ...

Multimode fibers (MMF) were initially developed to transmit digital information encoded in the time domain. There were few attempts in the late 60s and 70s to transmit analog images through MMF. With the availability of digital spatial modulators, practica ...

Recent advances on Vision Transformer (ViT) and its improved variants have shown that self-attention-based networks surpass traditional Convolutional Neural Networks (CNNs) in most vision tasks. However, existing ViTs focus on the standard accuracy and com ...

Deep Architectural Form

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Teachers’ Perspectives on Using and Teaching Artificial Intelligence in Early Primary Education

Learning Motion Reconstruction from Demonstration via Multi-Modal Soft Tactile Sensing

Teaching Not To

Tertiary Lymphoid Structures Generation Through Graph-Based Diffusion

Emergent coherent modes in nonlinear magnonic waveguides detected at ultrahigh frequency resolution

Scalable Personalized Education in the Age of GenAI: The Potential and Challenges of the PolyGloT Framework

Beyond neural data: Cognitive biometrics and mental privacy

Artificial intelligence and the local government: A five-decade scientometric analysis on the evolution, state-of-the-art, and emerging trends

Artificial intelligence of things for smart cities: advanced solutions for enhancing transportation safety

Wide-angle simulated artificial vision enhances spatial navigation and object interaction in a naturalistic environment

Explainability as fig leaf? An exploration of experts’ ethical expectations towards machine learning in psychiatry

Perspective Aware Road Obstacle Detection

Interpretable Representation Learning and Evaluation for Abstractive Summarization

A benchmark dataset for machine learning in ecotoxicology

4D printing of Metal-Reinforced double network granular hydrogels

From 3D to 2D and back again

Measurement in the Age of Information

Discriminative clustering with representation learning with any ratio of labeled to unlabeled data

Learning to image and compute with multimode optical fibers

Towards Robust Vision Transformer