Deep Learning conferences

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 Ghalamzan. The programme runs from 09:10 to 17:00 London time. Attendance costs £30 including lunch and refreshments.

ACML brings together research on the theory and practice of machine learning, with conference and journal publication tracks, invited talks, tutorials and workshops. The 2026 tutorial programme covers efficient and trustworthy reasoning with foundation models, robust statistical learning with alpha-divergence, topological deep learning, multimodal time series, generative methods for causal inference, distribution shifts, and continual learning toward self-evolving agents. Researchers from all regions are welcome. The event runs 1–4 December 2026. Its registration system lists an overall 08:00 start on 1 December and 17:30 finish on 4 December in Australia/Melbourne (AEDT, UTC+11). Tutorials and workshops are scheduled for 1 December. Current ticket prices including GST are AUD 1,030 for early full registration and AUD 666 for eligible student attendees without accepted main-track papers; later prices are AUD 1,250 and AUD 810. Author registration requirements depend on the number and track of accepted papers. Early rates and main-track author registration close 1 November at 23:59 Anywhere on Earth.

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.

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.

IJCNN covers neural-network foundations and intelligent applications, including continual and adaptive learning, forgetting mitigation, representation learning, explainability, neuromorphic computation, computational neuroscience and multimodal models. Research papers connect theoretical methods with applications across science and engineering. Review is double-blind. Standard submissions use six IEEE-format pages; up to four extra pages incur fees. Accepted authors must submit final papers and pay the corresponding registration fees by 12 April 2027, 23:59 AoE. Remote authors may supply prerecorded presentations, but the conference does not offer live remote attendance.