In this talk, we will voyage into uncharted territories where the latest in artificial intelligence converges with computational audio understanding and generation. It will unveil how cutting-edge deep learning techniques propel Computer Audition into unexplored dimensions. From unraveling complex ...

Björn W. Schuller received his diploma, doctoral degree, habilitation, and Adjunct Teaching Professor in Machine Intelligence and Signal Processing all in EE/IT from TUM in Munich/Germany where he is Full Professor and Chair of Health Informatics. He is also Full Professor of Artificial ...

In the past few years there has been an increasing interest in the application of Deep Learning techniques to various Information Retrieval tasks, among which Personalized Search. In this lecture, I will present an overview of the research undertaken in my research lab, related to the definition ...

Gabriella Pasi is professor of the University of Milano-Bicocca, and Head of the Department of Informatics, Systems and Communication, where she leads the Information and Knowledge Representation, Retrieval, and Reasoning (IKR3) research Lab. Her main research interests are related to Information ...

The Kepler and TESS missions have yielded an astounding 100,000 potential transit signals, paving the way for an intricate process of distillation to identify viable exoplanet candidates. In response to this formidable challenge, we introduce ExoMiner, a groundbreaking deep neural network ...

Holder a PhD in computer science with a focus in Machine Learning, Dr. Valizadegan has more than 20 years of experience in Artificial Intelligence and Machine Learning. He is a data science manager and machine learning lead at USRA and a senior machine learning scientist at NASA through NASA ...

The Cosmic Microwave Background (CMB) is a remnant radiation of the Big Bang, which is thought to mark the origin of the universe. The CMB anisotropies provides fundamental information about cosmology and on the initial conditions and the energy contents of the Universe. Therefore, it is very ...

Laura Bonavera achieved her Astrophysics PhD in 2011, supported by a fellowship from the International School for Advanced Studies (Italy) and a scholarship from CSIRO Astronomy and Space Science and the ATNF (Australia). Until 2015, she devoted her postdoctoral efforts to the ESA Planck mission ...

Text-to-audio generation aims to produce an audio clip based on a text prompt which is a language description of the audio content to be generated. This can be used as sound synthesis tools for film making, game design, virtual reality/metaverse, digital media, and digital assistants for text ...

Wenwu Wang is a Professor in Signal Processing and Machine Learning at the University of Surrey, UK. He is also an AI Fellow at the Surrey Institute for People Centred AI. His current research interests include signal processing, machine learning and perception, artificial intelligence, machine ...

Large-scale training of neural networks with self-supervision has allowed us to obtain robust data representations on nearly any domain. Features computed with DINOv2 show very strong performance on many benchmarks, meeting the quality of CLIP-like models on categorization tasks and setting a new ...

Piotr Bojanowski is Research Scientist at Meta. He is interested in applications of machine learning to Computer Vision and Natural Language Processing. His main research interests are focused on large-scale unsupervised learning. Co-creator of the fastText library designed to help build scalable ...

Marked Temporal Point Processes (TPPs) are a valuable tool for modeling continuous-time event sequences and predicting the arrival time and type of future events. Neural TPPs leverage the expressive power of neural networks to address the limitations of classical TPP models, such as the Hawkes ...

Souhaib Ben Taieb is an Associate Professor of Machine Learning and Data Science at the University of Mons (UMONS) in Belgium, leading the Big Data and Machine Learning Lab. His research encompasses various aspects of probabilistic machine learning for time series data, spanning topics such as ...

Object Cluster Hierarchy – a new variant of Hierarchical Cluster Analysis is presented. Object Cluster Hierarchy (OCH) is an extension of the Hierarchical Clustering (HC) paradigm, considering Human perception of hierarchical data. Even though OCH is at an early stage of development, an ...

Halina Kwaśnicka is a Computer scientist specializing in artificial intelligence and a professor at the Department of Artificial Intelligence, Wroclaw University of Science and Technology, Poland. In 2023, the Rector of Wrocław University of Science and Technology, Prof. Arkadiusz Wójs, granted ...

Large Language Models (LLMs) have demonstrated tremendous capabilities in solving complex tasks. However, they sometimes suffer from confabulations, which can result in incorrect facts. This hinders their ability to contribute to new scientific discoveries. This talk will introduce FunSearch (short ...

Mohammadamin Barekatain is a former senior research engineer at Google DeepMind. Since early 2024, he has been a quantitative developer at Quadrature in London. He earned his master’s degree in computer science with the highest honours from the Technical University of Munich. His research ...