
۰۳ اردیبهشت - ۰۵ اردیبهشت ۱۴۰۴
European Symposium on Artificial Neural Networks
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نمای کلی
The 33rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2025) will be held in a hybrid format from April 23-25, 2025. The conference will take place in Bruges, Belgium, with an online participation option. ESANN is a key event for researchers in artificial neural networks, computational intelligence, machine learning, and related fields.
Call for papers
Scope and Topics
Since its first happening in 1993, the European Symposium on Artificial Neural Networks (ESANN) has become the reference for researchers on fundamentals and theoretical aspects of artificial neural networks, computational intelligence, machine learning and related topics. ESANN conferences cover artificial neural networks, machine learning, statistical information processing and computational intelligence. Mathematical foundations, algorithms and tools, and applications are covered.
The ESANN 2025 conference will follow this tradition, while adapting its scope to the recent developments in the field.
Topics Covered
The following is a non-exhaustive list of machine learning, computational intelligence and artificial neural networks topics covered during the ESANN conferences:
- Neural networks
- Deep learning
- Kernel machines
- Signal processing and modeling
- Transfer learning
- Graphical models, EM and Bayesian learning
- Classification and clustering
- Vector quantization and self-organizing maps
- Recurrent networks and dynamical systems
- Time series forecasting
- Single- and zero-shot learning
- Ensemble learning
- Feature selection
- Graphs and networks
- Nonlinear dimensionality reduction; manifold learning
- Statistical and mathematical aspects of learning
- Trustworthy AI
- Image processing
- Natural Language Processing
- Data mining
- Machine learning for signal processing
- Multimodal interfaces and multichannel processing
- Vision and sensory systems
- Data visualization
- Identification of non-linear dynamical systems
- Machine learning for healthcare
- Evolutionary computation for machine learning
- Bioinformatics
- Bio-inspired systems
- Brain-computer interfaces
Special Sessions
Special sessions will be organized by renowned scientists in their respective fields. Papers submitted to these sessions are reviewed according to the same criteria as the submissions to the regular sessions. Authors who submit a paper to one of these sessions are invited to mention it on the author submission form. Submissions to regular and special sessions follow identical format, instructions, deadlines and procedures. See the special sessions page for details about the special sessions organized during ESANN 2025.
Talks and Posters
Accepted papers are presented either as talks or posters. Authors may indicate their preference at submission; however as ESANN is a single-track conference, the number of slots for talks is limited. All poster presentations are coupled to a one-minute spotlight oral presentation during a plenary session; poster presentations increase the interaction with participants.
There is no difference in scientific quality between talks and posters. The reviewing and selection processes are identical. In addition, all full papers are published in the same way in the proceedings, regardless of the mode of presentation.
Deadlines
Prospective authors are invited to submit their contributions before 27.11.2024 (extended submission deadline).
- Decisions: 24.01.2025
- Conference: 23.04.2025 - 25.04.2025
Format of the Conference
The 33th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning will be organized in hybrid mode. Both in-person and online participation will be possible.
Publication
All full papers are published in the proceedings.
تاریخهای مهم
تاریخهای کنفرانس
Conference Date
۳ اردیبهشت ۱۴۰۴ → ۵ اردیبهشت ۱۴۰۴
ارسال مقاله
Extended submission deadline
۷ آذر ۱۴۰۳
اعلان
Decisions
۵ بهمن ۱۴۰۳
رتبه منبع
منبع: CORE2023
رتبه: B
حوزه پژوهشی: Machine learning