Biological systems understand the world by simultaneously processing high-dimensional
inputs from modalities as diverse as vision, audition, touch, proprioception, etc. The perception …

The Hamiltonian formalism plays a central role in classical and quantum physics. Hamiltonians
are the main tool for modelling the continuous time evolution of systems with conserved …

The ability to learn universal audio representations that can solve diverse speech, music,
and environment tasks can spur many applications that require general sound content …

A central goal of machine learning is the development of systems that can solve many
problems in as many data domains as possible. Current architectures, however, cannot be …

The promise of self-supervised learning (SSL) is to leverage large amounts of unlabeled
data to solve complex tasks. While there has been excellent progress with simple, image-level …

Real-world data is high-dimensional: a book, image, or musical performance can easily
contain hundreds of thousands of elements even after compression. However, the most …

The rapid progress in artificial intelligence (AI) and machine learning has opened
unprecedented analytics possibilities in various team and individual sports, including baseball, …

We present a general-purpose framework for image modelling and vision tasks based on
probabilistic frame prediction. Our approach unifies a broad range of tasks, from image …

An essential task of the auditory system is to discriminate between different communication
signals, such as vocalizations. In everyday acoustic environments, the auditory system needs …

10.7554/eLife.47596.001 Most accounts of image and object encoding in inferotemporal
cortex (IT) focus on the distinct patterns of spikes that different images evoke across the IT …