相关论文: Enhancement Programming Skills and Transforming Kn…
Deep learning methods have recently made notable advances in the tasks of classification and representation learning. These tasks are important for brain imaging and neuroscience discovery, making the methods attractive for porting to a…
Recently, both industry and academia have proposed several different neuromorphic systems to execute machine learning applications that are designed using Spiking Neural Networks (SNNs). With the growing complexity on design and technology…
Deep learning methods are increasingly being applied to problems in medicine and healthcare. However, few epidemiologists have received formal training in these methods. To bridge this gap, this article introduces to the fundamentals of…
Context: As the demand for digital solutions adapted to different user profiles increases, creating more inclusive and diverse software development teams becomes an important initiative to improve software product accessibility. Problem:…
Concept probing has recently garnered increasing interest as a way to help interpret artificial neural networks, dealing both with their typically large size and their subsymbolic nature, which ultimately renders them unfeasible for direct…
If a person can solve a task, can measuring their brain make it easier to train a model to solve that task too? Recent NeuroAI work suggests that supplementing task training with neural recordings can modestly improve model performance and…
The current processes for building machine learning systems require practitioners with deep knowledge of machine learning. This significantly limits the number of machine learning systems that can be created and has led to a mismatch…
Educational Data Mining (EDM) has emerged as a vital field of research, which harnesses the power of computational techniques to analyze educational data. With the increasing complexity and diversity of educational data, Deep Learning…
Software has eaten the world with many of the necessities and quality of life services people use requiring software. Therefore, tools that improve the software development experience can have a significant impact on the world such as…
Binary program comprehension is critical for many use cases but is difficult, suffering from compounded uncertainty and lack of full automation. We seek methods to improve the effectiveness of the human-machine joint cognitive system…
In this chapter we first outline some of the popular computing environments used for analysing neural data, followed by a brief discussion of 'software carpentry', basic tools and skills from software engineering that can be of great use to…
In today's education systems, there is a deep concern about the importance of teaching code and computer programming in schools. Moving digital learning from a simple use of tools to understanding the processes of the internal functioning…
Psycholinguistics and neurolinguistics are two complementary disciplines that study language from different perspectives. Psycholinguistics focuses on the cognitive processes involved in language production and comprehension, while…
As Artificial Intelligence (AI) increasingly impacts professional practice, there is a growing need to AI-related competencies into higher education curricula. However, research on the implementation of AI education within study programs…
This paper presents an approach to the study of cognitive activities in collaborative software development. This approach has been developed by a multidisciplinary team made up of software engineers and cognitive psychologists. The basis of…
Program comprehension concerns the ability of an individual to make an understanding of an existing software system to extend or transform it. Software systems comprise of data that are noisy and missing, which makes program understanding…
In pursuit of enhancing the predication capabilities of the neural network, it has been a longstanding objective to create dataset encompassing a diverse array of samples. The purpose is to broaden the horizons of neural network and…
The past few years have seen remarkable progress in the decoding of speech from brain activity, primarily driven by large single-subject datasets. However, due to individual variation, such as anatomy, and differences in task design and…
High-resolution neural datasets enable foundation models for the next generation of brain-computer interfaces and neurological treatments. The community requires rigorous benchmarks to discriminate between competing modeling approaches, yet…
This chapter explores the ways in which organisational readiness and scientific advances in Artificial Intelligence have been affecting the demand for skills and their training in Australia and other nations leading in the promotion, use or…