Predictive models

This half-day workshop debates when explicit predictive models improve robot learning and when end-to-end policies or hybrid systems are preferable. Six debate motions examine generalization, counterfactual reasoning, data efficiency, evaluation, deployment costs and the limits of current benchmarks. Invited talks, contributed spotlights and posters connect theory to empirical comparisons, including negative results. Confirmed speakers include Chelsea Finn, Yunzhu Li, Georgia Chalvatzaki and Vincent Sitzmann. Paper submissions closed on 12 October; camera-ready papers are due on 6 November and

…strain diversity using statistical models, and supports predictive models of natural soils and synthetic microbial communities. The full-time appointment lasts three years, with extension dependent on funding and performance. Salary is £39,000–£42,150 at postdoctoral level or £47,450–£52,560 at senior level; senior appointment requires substantial metagenomics and research-leadership experience.

This one-day symposium examines learned predictive models that support simulation, planning and policy learning. It connects generative and interactive video, latent predictive architectures, three- and four-dimensional scene representations, reinforcement learning and model-predictive control. Invited talks and contributed presentations address applications to games, robot manipulation and autonomous driving, together with the foundations and evaluation of world models. Speakers include Amir Bar, Viorica Pătrăucean, Katja Hofmann, Vassia Simaiaki, Niloy Mitra, Andrea Vedaldi and Amir Ghalamza

This Notice of Funding Opportunity (NOFO) supports transdisciplinary research teams seeking to develop mechanistic, biologically grounded explanations of how neural circuits and their cellular building blocks give rise to central nervous system (CNS) function. Teams must integrate expertise spanning molecular and cellular through systems neuroscience, with strong collaboration between experimental and computational investigators, to bridge cells, circuits, and behavior in a unified framework that yields mechanistic insight.Applications must explicitly connect three core elements: (1) character

AI systems increasingly influence both which images people encounter and predictions of how those images attract attention. This session examines the relationship between automated image selection, predicted visual attention and measured human responses. Peter Steidl presents Visual GEO and a two-stage account of visual communication: an image must first be recognized and selected by a machine before human attention can be measured. Hedda Martina Šola compares machine predictions with human measurements in two published studies using the same material, including a case where an AI-created des

…advanced theories, mechanistic or predictive models, and computational or statistical methods that improve quantitative understanding of brain function across scales. Tools must address complex neural and behavioral data and be made broadly available to the neuroscience research community.

While several methods exist for clustering neurons based on their selectivity to specific visual features, the extent to which neurons form clusters based on their invariances - how neurons maintain consistent responses despite variations in visual input - remains largely unexplored. Clustering neurons based on their invariances, however, presents several challenges, including the identification of directions in the stimulus space along which a neuron exhibits invariance (i.e., consistent response), and the comparison and alignment of such non-trivial trajectories to assess whether neurons exh

Natural language is strongly context-dependent and can be perceived through different sensory modalities. For example, humans can easily comprehend the meaning of complex narratives presented through auditory speech, written text, or visual images. To understand how complex language-related information is represented in the human brain there is a necessity to map the different linguistic and non-linguistic information perceived under different modalities across the cerebral cortex. To map this information to the brain, I suggest following a naturalistic approach and observing the human brain p