Mitigating Label Biases for In-context Learning

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Aircraft-based monitoring of wildlife is a popular way among conservation practitioners to obtain animal population counts over large areas. Nowadays, these aerial censuses are becoming increasingly scalable due to the advent of drone technology, which is ...

The generation of synthetic patient data that reflect the statistical properties of real data plays a fundamental role in today’s world because of its potential to (i) be enable proprietary data access for statistical and research purposes and (ii) increas ...

Symmetry is one of the most central concepts in physics, and it is no surprise that it has also been widely adopted as an inductive bias for machine-learning models applied to the physical sciences. This is especially true for models targeting the properti ...

Intelligent Tutoring Systems (ITS) enhance personalized learning by predicting student answers to provide immediate and customized instruction. However, recent research has primarily focused on the correctness of the answer rather than the student's perfor ...

According to the proposed Artificial Intelligence Act by the European Comission (expected to pass at the end of 2023), the class of High-Risk AI Systems (Title III) comprises several important applications of Deep Learning like autonomous driving vehicles ...

Wind farm modelling is an area of rapidly increasing interest with numerous analytical and computational-based approaches developed to extend the margins of wind farm efficiency and maximise power production. In this work, we present the novel ML framework ...

Image super-resolution is a classic ill-posed computer vision and image processing problem, addressing the question of how to reconstruct a high-resolution image from its low-resolution counterpart. Current state-of-the-art methods have improved the perfor ...

Education is an art close to theater. A teacher is taking a role; he works his speeches and his gestures and he plays with the attention of his audience. But it is harder: more than entertaining, a teacher must shape the skills, the knowledge and the motiv ...

Stereo matching aims to perceive the 3D geometric configuration of scenes and facilitates a variety of computer vision in advanced driver assistance systems (ADAS) applications. Recently, deep convolutional neural networks (CNNs) have shown dramatic perfor ...

In the biometrics community, face and speaker recognition are mature fields in which several systems have been proposed over the past twenty years. While existing systems perform well under controlled recording conditions, mismatch caused by the use of dif ...

Mitigating Label Biases for In-context Learning

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How to minimize the annotation effort in aerial wildlife surveys

Generative models for synthetic data generation: application to pharmacokinetic/pharmacodynamic data

Probing the effects of broken symmetries in machine learning

Student Answer Forecasting: Transformer-Driven Answer Choice Prediction for Language Learning

Robust Training and Verification of Deep Neural Networks

Accelerated wind farm yaw and layout optimisation with multi-fidelity deep transfer learning wake models

Context-Aware Image Super-Resolution Using Deep Neural Networks

Mutual Understanding in Educational Human-Robot Collaborations

Unsupervised Stereo Matching Using Confidential Correspondence Consistency

Scalable Probabilistic Models for Face and Speaker Recognition