Machine Learning workshops

The training school develops three foundations for AI in scientific computing. Daniel Bartl introduces statistical learning through high-dimensional probability, explaining how the geometry and complexity of function classes govern generalization. Stanislav Budzinskiy covers floating-point errors, deterministic and stochastic rounding, matrix multiplication, mixed precision and conditioning in neural-network training and inference. Maximilian Herde introduces neural operators and foundation models for partial differential equations, studying pretraining, scaling and transfer to new physical problems, with practical Python exercises. The school meets in person at RICAM, Science Park 2, fourth floor, Altenberger Straße 69, Linz, on 5–9 October. Monday through Thursday lectures start at 09:00 and run to 12:30, with discussion and exercise sessions generally scheduled 13:30–17:00; Wednesday has an excursion. Friday’s lectures run 09:00–11:30. Times are Europe/Vienna, CEST (UTC+02:00). The registration form still lists the Training School and requires an institutional email address. Registration is binding; participants should review the organizer’s cancellation and non-attendance policy. The event begins shortly after this listing’s publication.

This RICAM workshop examines the numerical foundations of reliable deep-learning computation. Low-precision and mixed-precision arithmetic, quantization and parallel GPU computation enable larger models and deployment on constrained devices, while introducing questions about error, stability and performance. Researchers from theoretical and applied communities will compare methods for stable training and efficient inference and identify directions for further work. The programme brings together expertise in numerical analysis, machine learning and hardware-aware computation. The in-person workshop runs on 2–6 November at RICAM, Science Park 2, fourth floor, Altenberger Straße 69, Linz. Monday registration and welcome run 14:00–14:40, followed by talks until 17:00. Tuesday through Friday sessions begin at 09:00; Friday’s programme ends at 11:40. Times are Europe/Vienna, CET (UTC+01:00). Register through the special-semester form, select Workshop 2 and Regular Participant, and use an institutional email address to verify affiliation. Registration is binding; the organizer asks for cancellation at least one week before the workshop and states that unreported non-attendance can exclude participants from future events.

This online workshop connects computational neuroscience, machine learning and neuromorphic engineering through research on spiking neural networks. It examines artificial and biologically plausible learning algorithms and how trained spiking circuits can reveal principles of neural processing. Two afternoons combine four invited talks, seven contributed-talk slots, flash presentations and a virtual poster session, with time for discussion. Invited speakers are Susanne Schreiber, Mihai Petrovici, Eugene Izhikevich and Giulia D’Angelo. The programme begins at 14:00 CET on both 4 and 5 November; the first day reaches posters at 17:30, and the second concludes with remarks at 17:25. Attendance is free with registration to receive streaming links. The abstract deadline was 25 September 2026. Ticket sales end on 4 November 2026.

Researchers from neuroscience, engineering and clinical practice will examine technologies for understanding brain function and treating disorders. Three tracks cover emerging neural recording and imaging methods, machine learning and brain-inspired computation, and clinical translation through neuroprosthetics, neuromodulation and brain-computer interfaces. The programme connects multiscale measurement, interpretable models, multimodal data and biomarkers with deployment challenges. Panels consider ethics, standards, clinical needs, careers and funding; posters, live demonstrations, exhibits and an aging-brain symposium support exchange. In-person at the National Housing Center, 1201 15th St NW, Washington, DC 20005, November 11–13. All times are US Eastern (America/New_York): November 11 registration 12:00, activities 13:00; November 12–13 registration 08:00, sessions 08:30; closing events end November 13 at 18:00. Regular fees: IEEE members USD 425, non-members USD 475; students USD 50/75 respectively. Early rates ended October 1. General poster/demo abstracts close October 19. Member and non-member registration is available through the event website.