Machine Learning conferences

SAB 2026 investigates the mechanisms that let natural and artificial agents adapt and survive in uncertain environments. Researchers compare biological behavior with robot experiments, computer simulations and mathematical models to evaluate principles and architectures of adaptive behavior. The programme covers collective intelligence, learning and skill acquisition, artificial perception and manipulation, and physical and social constraints on behavior. A cross-kingdom intelligence symposium includes Paco Calvo, Jens Krause, Vera Meyer and Ute Schmid. The meeting runs 19–22 October 2026 in Berlin, on CEST (Europe/Berlin, UTC+2). Workshops on 19 October at TU Berlin, Marchstraße 23, start at 09:00 following registration at 08:15; afternoon workshops end at 18:30. Topics include internal world models, genetic programming and homeostatic control. Conference sessions on 20–22 October take place at Universität der Künste, Georg-Neumann-Saal, Einsteinufer 43; sessions on 20 and 21 October begin at 09:00. Consult the detailed daily programme for session and venue changes. Public registration through Pretix is open. General admission is EUR 550, or EUR 450 for students with proof of status. Fees include sessions, coffee breaks and one networking dinner; lunches, other dinners and optional social activities are self-funded. No VAT is added.

The 2026 Conference on Empirical Methods in Natural Language Processing, organized by ACL's SIGDAT, held October 24-29, 2026 in Budapest, Hungary, with a main conference plus workshops and tutorials.

This meeting critically examines whether ecological forecasting can become accurate enough for conservation and biodiversity management. Demographic and ecosystem models, observations, statistical inference and machine learning address interacting species under climate and other pressures. Terrestrial, marine and polar examples explore predictability limits, uncertainty, model benchmarking and research-informed decisions. Programme participants include Emily G Simmonds (University of Edinburgh, UK); Benjamin Planque (Institute of Marine Research, Norway); Michael Dietze (Boston University, US); Stéphanie Jenouvrier (Woods Hole Oceanographic Institution, US); Owen Petchey (University of Zurich, Switzerland); Marlène Gamelon (University of Lyon, France). Schedule: 2–3 November 2026, 09:00–17:00 each day, Europe/London (GMT, UTC+0). Researchers may attend online or at the Royal Society, 6–9 Carlton House Terrace, London SW1Y 5AG, United Kingdom. Both modes are free; advance registration is required using the appropriate online or in-person ticket. Optional lunch is £25/day, subject to availability; outside food is permitted. Poster proposals for 2 November, including an abstract up to 200 words, are due 16 October 2026; acceptance is rolling.

Researchers and practitioners will discuss mathematical foundations of data science, including high-dimensional geometry, dimensionality reduction, scalable algorithms, uncertainty and machine learning. The conference takes place in person at the Salt Palace Convention Center on 16–20 November 2026. Registration is open, with early rates through 19 October; abstract and travel-support deadlines have passed. Registration also covers the co-located SIAM Imaging Science and Data Mining conferences.

This meeting examines how brain-inspired hardware could reduce AI’s growing energy requirements. Researchers connect materials and memory devices with circuits, systems and applications, including sparse computation and compute-in-memory architectures that reduce data movement. Two discussion days address fundamental advances and challenges; the final day considers translation and wider impacts. Programme participants include Steve Furber, Judith Driscoll and Tony Kenyon. The meeting takes place at The Royal Society, 6–9 Carlton House Terrace, London SW1Y 5AG, or online, on 23–25 November 2026. Times are GMT (Europe/London, UTC+0). Sessions run 09:00–17:00 on 23 and 24 November, with posters 17:00–18:00 on 23 November; the 25 November programme runs 09:30–15:15. Timings may change. Attendance is free for researchers in relevant fields, with advance Eventbrite registration required. Separate online and in-person tickets cover the discussion meeting and final-day event; attending every day is optional. Lunch costs an optional GBP 25 on each of the first two days and is free on the third. Poster proposals are due 23 October, subject to capacity.

Under the theme Aspiration, Action, Anticipation: AI for Science Looking to 2030, this summit asks how AI is already changing scientific practice and how research may develop over the next few years. Researchers will examine scientific reasoning and discovery alongside applications in cancer biology, climate and weather prediction, animal behaviour and cosmology. Talks, discussion and a poster session connect methodological advances with practical scientific problems. Confirmed contributors include Max Welling, Hana Aliee, Boris Bolliet, Cait Newport, Richard Turner, Neil Lawrence, Stephen Roberts and Sadiq Jaffer. The summit takes place on 24 November, 10:00–18:00, at Churchill College, Cambridge; times are Europe/London, GMT (UTC+00:00). The organizer’s event-specific registration form confirms that online participation is available for remote attendees. In-person places are limited and offered first come, first served, with a waiting list once full. Register using the linked Microsoft Form.

The fourth Breaking Topics in AI conference brings researchers from Oxford, UCL, Cambridge and Imperial together to examine recent AI advances and open research challenges. Plenary speakers give overviews of developments in their fields, while paper talks discuss selected recent work from ICML and NeurIPS. The programme combines perspectives from Mark van der Wilk, Maneesh Sahani, Jacob Bamberger, Vignesh Gopakumar and Katarzyna Kobalczyk, creating opportunities to connect new methods with ongoing research across the participating institutions. This free, in-person conference takes place on 25 November in LRT 608 A+B, Level 6 of I-HUB, White City Campus, 84 Wood Lane, London. Doors open at 09:00 and the ticket page schedules the event for 09:30–17:00, within the university’s overall 09:00–17:00 listing. Times are Europe/London, GMT (UTC+00:00). Advance registration is required through the Eventbrite link on the official university page; capacity is limited and the ticket page specifies ages 16 and above.

The Fortieth Annual Conference on Neural Information Processing Systems brings together interdisciplinary machine-learning research through peer-reviewed sessions, invited talks, demonstrations, tutorials, workshops, and an exposition.

The Fortieth Annual Conference on Neural Information Processing Systems, organized by the Neural Information Processing Systems Foundation, with the main meeting in Sydney, Australia (Dec 6-12) and satellite venues in Atlanta, Georgia and Paris, France (Dec 9-13).

The 41st Annual AAAI Conference on Artificial Intelligence at the Palais des Congres de Montreal, featuring technical papers, special tracks, invited speakers, workshops, tutorials, poster sessions, and competitions to promote AI research and scientific exchange.

SIAM’s computational science and engineering meeting covers mathematical models, scalable algorithms, scientific software, high-performance computing and scientific machine learning. It takes place in Pittsburgh on 22–26 February 2027. Travel-support applications are open until 30 November 2026. Abstract deadlines have passed; registration is scheduled to open in December 2026. The meeting is co-located with ACDA27 and the International Meshing Roundtable.

AISTATS brings together machine learning, artificial intelligence and statistics, with an emphasis on methodological research. The 2027 conference is announced for 3–6 May in Montréal, Canada; the specific venue and registration details remain to be announced. The official schedule lists abstract submissions due 29 September 2026 and full papers due 6 October 2026, both at the end of the day Anywhere on Earth.

EMBO | EMBL Symposium bringing machine-learning and life-science researchers together across sequencing, imaging and structural biology. Topics include foundation models, cross-modality learning, causal explanation, mechanistic interpretability, generative models and AI agents. Onsite workshops and tutorials take place on the first day; the following three days offer hybrid talks and posters. Registration is not yet open; the official page accepts expressions of interest.

The Society for Industrial and Applied Mathematics convenes its triennial conference on applied and numerical linear algebra. The programme covers matrix computations, machine learning, quantum simulation, inverse problems, high-performance computing, dynamical systems, model reduction, optimal transport, network science, tensor methods and related applications. Proposal submissions are currently open, with minitutorial and minisymposium proposals due 26 October 2026 and contributed presentation abstracts due 23 November 2026.