Machine Learning conferences

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.

This one-day British Machine Vision Association technical meeting, the UK chapter of the international AI for Visual Arts (AI4VA) series, brings together researchers, artists, curators and industry practitioners to explore how AI, machine learning and computer vision are reshaping the visual arts, with emphasis on creative content generation, cultural heritage and the animation and creative industries. Vision methods built around photorealistic data struggle with the abstraction, stylisation and narrative structure of paintings, comics, illustration and sculpture, while generative models raise open questions of controllability, provenance, authorship and alignment with artistic intent. Topics include generative models for art and design, sketch-based interfaces, AI for animation and visual effects, perception of non-photorealistic content, computer vision for cultural heritage digitisation and restoration, vision-language models for art interpretation, neural rendering and 3D Gaussian splatting, human-AI co-creation, provenance and authenticity verification, style transfer and computational art analysis, and the ethics of AI-generated art. Chaired by Deblina Bhattacharjee, the meeting features keynotes including Yi-Zhe Song and Neill Campbell, contributed presentations, poster and demo sessions and a panel discussion. The event is in person only; registration costs £30 including lunch and refreshments.

The Northern Lights Deep Learning Conference (NLDL) gathers national and international researchers in Tromsø to exchange ideas, encourage collaboration and present cutting-edge deep learning research. The 2027 edition is an in-person conference organised by Visual Intelligence and the UiT Machine Learning Group, with peer-reviewed full papers published in the Proceedings of Machine Learning Research, non-archival extended abstracts, an industry event and a Diversity in AI event. Topics span general deep learning (architectures, generative models, deep reinforcement learning), related machine learning (active, online, self-supervised learning and time-series analysis), optimisation, Bayesian and variational methods, graphical models and explainability, applications to vision, language, signals, speech and audio, and deep learning for the sciences, including biology and medicine, environment and ecology, and physics. The main conference runs 12-14 January 2027; the surrounding NLDL Winter School (11-15 January), part of the NORA Research School and worth 2.5 ECTS, offers tutorials on agentic AI and AI-assisted research, deep ordinal representations for trustworthy AI, evaluating large language models beyond accuracy, and Arctic AI-Earth system modelling and evaluation.

This one-day British Machine Vision Association technical meeting brings academic and industry researchers together on all aspects of interpretability in computer vision and its applications. Topics include what comes next for interpretability in vision, mechanistic interpretability and circuit discovery, post-hoc analysis after training, interpretable-by-design methods, language-based and multimodal techniques, white-box versus black-box approaches, making foundation models interpretable, datasets and evaluation metrics, understanding representations for explainable models, model intervention, robustness and scalability, and real-world applications. Chaired by Davide Moltisanti and Michael Wray, the tentative programme (09:00-17:00) includes invited talks by Oisin Mac Aodha, Elisa Ricci and Stephan Alaniz, accepted talks, poster sessions and an interactive closing session. Presentations may cover published or ongoing work as talks or posters; expressions of interest to present are due by 26 November 2026. The event is in person only; registration costs £30 including lunch and refreshments.

The 2027 Quantitative Genetics and Genomics Gordon Research Conference, "Use of Machine Learning and Artificial Intelligence in Quantitative Genetics", starts from the observation that linear models remain the bedrock of quantitative genetics, used to estimate genetic parameters and build prediction models such as polygenic risk scores, while machine learning and AI have transformed simulation, complex data analysis and prediction elsewhere but remain little used in the field. The meeting debates whether there are fundamental reasons for this and what ML and AI can offer for simulating genomes and phenotypes, modelling polygenic traits and elucidating the biology of complex traits and disease. Sessions include the roles of AI, generative AI and ML in simulation studies and complex-trait prediction with ML methods, with work spanning human and animal genetics. The five-day meeting combines talks on unpublished work with extended discussion, poster sessions open to all career stages, and communal meals and free afternoons for informal exchange; attendance is by application.

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.

The 2027 Gas Sensing and Artificial Olfaction Gordon Research Conference, "Chemoresponsive Materials and Algorithms for Gas Sensing in Healthcare and Robotics", covers a field at the intersection of materials science, chemical engineering, data science and biology. Central themes are advanced nanomaterials and microporous frameworks for selectivity and sensitivity, atomically dispersed elements for tunable surface reactivity, carbon-based sensing platforms, and bioinspired and biomimetic approaches that emulate biological odour discrimination. Machine learning applied to gas-sensor datasets for real-time, high-dimensional pattern recognition is a parallel focus, with applications in wearable and portable devices, medical diagnostics from non-invasive breath analysis to early disease detection, and robotic olfaction systems that navigate and map volatile environments. Researchers from academia, industry, start-ups and clinical practice take part. The five-day meeting combines talks on unpublished work with extended discussion, poster sessions open to all career stages, and communal meals and free afternoons for informal exchange; attendance is by application.

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.

The inaugural RACI conference on robotics, automation and machine learning in chemistry examines robotic synthesis, automated analysis, experimental planning, self-driving laboratories and chemical data science. Academic and industry researchers will exchange methods through plenary and contributed talks, posters and demonstrations. The meeting connects chemistry with robotics and AI, including cheminformatics and data-driven discovery. Paid registration includes the two-day programme, welcome reception and daytime catering; the conference dinner costs extra. Abstract submissions close on 31 October 2026, with acceptance notices on 15 November and early-bird rates through 30 November. The RACI registration table gives 18 February 2027 as the final registration date.

The meeting connects computation with the stages of drug development. Researchers examine generative models, language models and multimodal methods alongside experimental biology, pharmacology and clinical evidence, addressing challenges in targets, efficacy, safety and translation across patient populations.

Bring together materials researchers, chemists, artificial-intelligence specialists and philosophers to examine how machine learning, generative modelling, robotic laboratories and advanced characterisation change the discovery of functional materials. Discussion will connect emerging opportunities to experimental validation, scientific understanding and the practical transition from prediction to application. The meeting is intended for researchers in relevant fields, with free virtual and in-person attendance and advance registration required. Optional lunch costs £25 per day. Poster abstracts of up to 200 words are due on 2027-02-19; the session takes place on the first day.