International Joint Conference on Neural Networks

International Joint Conference on Neural Networks
Name	International Joint Conference on Neural Networks
Acronym	IJCNN
Discipline	Artificial intelligence; Machine learning; Neuroscience
First	1987
Frequency	Annual
Organizers	Institute of Electrical and Electronics Engineers; International Neural Network Society; European Neural Network Society
Country	International

International Joint Conference on Neural Networks is an annual academic conference bringing together researchers from Institute of Electrical and Electronics Engineers, International Neural Network Society, European Neural Network Society, Centre National de la Recherche Scientifique and industry labs such as IBM Research, Google Research, Microsoft Research, DeepMind for presentations on neural computation, deep learning, and computational neuroscience. The conference has attracted keynote speakers affiliated with Massachusetts Institute of Technology, Stanford University, University of Toronto, University of California, Berkeley and published proceedings alongside venues like NeurIPS, ICML, AAAI, ACL and CVPR.

History

IJCNN was established in 1987 amid collaborations among IEEE units, International Neural Network Society, European Neural Network Society and early neural research groups at Bell Labs, SRI International, Los Alamos National Laboratory and Hewlett-Packard to coordinate research that built on work from Frank Rosenblatt, David Rumelhart, Geoffrey Hinton, Yann LeCun and Juergen Schmidhuber. Early meetings featured communities connected to CERN, NASA, DARPA, National Institutes of Health and laboratories such as AT&T Bell Laboratories and Mitsubishi Electric Research Laboratories while drawing attendees from universities like Carnegie Mellon University, University of Edinburgh, University of Tokyo and University of Cambridge. Throughout the 1990s and 2000s the conference paralleled developments reported at Cognitive Science Society meetings, Society for Neuroscience symposia, and the growth of startups influenced by founders from Stanford University and Massachusetts Institute of Technology. Recent decades saw cross-fertilization with publications from Nature, Science, PNAS, IEEE Transactions on Neural Networks and Learning Systems and collaborations with research centers such as Allen Institute for Brain Science, Howard Hughes Medical Institute, Facebook AI Research.

Organization and Governance

IJCNN is jointly sponsored by the Institute of Electrical and Electronics Engineers and the International Neural Network Society with program committees drawn from members of European Neural Network Society, Japanese Neural Network Society, Chinese Association for Artificial Intelligence and research institutions like Max Planck Society, National University of Singapore, Tsinghua University and ETH Zurich. Governance includes steering committees, executive boards, and technical program chairs often affiliated with California Institute of Technology, Imperial College London, Peking University and Seoul National University who coordinate peer review modeled after procedures at ACM SIGGRAPH, IEEE CVPR and ACL. Financial and legal oversight involves partnerships with organizations such as Society for Industrial and Applied Mathematics, Royal Society, National Science Foundation and corporate sponsors including Intel, NVIDIA, Amazon Web Services.

Conferences and Locations

IJCNN has rotated venues worldwide including cities with major research hubs such as Honolulu, Montreal, Barcelona, Beijing, Prague, Melbourne, San Diego, Seattle, Lisbon and Buenos Aires, often co-located with workshops tied to NeurIPS Workshop series, ICLR Workshop tracks and symposiums at Royal Society venues. Host institutions have included University of Hawaii, McGill University, Universitat Politècnica de Catalunya, Tsinghua University, Charles University, University of Melbourne, University of California, San Diego, University of Washington, University of Lisbon and Universidad de Buenos Aires. Special sessions have been organized in partnership with national agencies such as European Commission, Japan Science and Technology Agency, National Natural Science Foundation of China and Australian Research Council.

Proceedings and Publications

Proceedings of IJCNN have been published under IEEE Xplore and indexed in databases alongside articles in IEEE Transactions on Neural Networks and Learning Systems, Neurocomputing, Journal of Machine Learning Research, Pattern Recognition and archived with organizations such as arXiv, DBLP, Scopus and Web of Science. The conference has produced special issues in journals including Nature Machine Intelligence, Frontiers in Neuroscience, IEEE Signal Processing Magazine and curated volumes associated with publishers like Springer, Elsevier and MIT Press.

Topics and Scope

IJCNN covers topics spanning connections to research at Cold Spring Harbor Laboratory, Salk Institute, Broad Institute and methods prominent in work by Yoshua Bengio, Andrew Ng, Ian Goodfellow, Ruslan Salakhutdinov and Demis Hassabis. Typical topics include architectures influenced by Convolutional Neural Networks research at Yann LeCun's lab, recurrent models relevant to Eugene M. Izhikevich and Walter Freeman-inspired dynamics, reinforcement learning connected to Richard Sutton and Andrew Barto, unsupervised learning and representation learning linked to Geoffrey Hinton and Ilya Sutskever, neuromorphic computing associated with IBM TrueNorth, SpiNNaker and Intel Loihi, and interpretability tied to initiatives at OpenAI, DeepMind and Google DeepMind.

Awards and Distinguished Lectures

IJCNN confers awards and lectures often recognizing researchers from institutions such as Massachusetts Institute of Technology, Stanford University, University of Toronto, University College London and University of Oxford and honoring contributions similar to the Turing Award, IEEE Frank Rosenblatt Award, ACM SIGKDD Innovation Award and lectures modeled on Royal Society Lecture series. Distinguished lectures have been delivered by figures associated with Geoffrey Hinton, Yann LeCun, Demis Hassabis, Jürgen Schmidhuber and Terrence Sejnowski alongside panels featuring representatives from Google Research, Microsoft Research, Facebook AI Research and OpenAI.

Impact and Contributions to the Field

IJCNN has influenced developments reported in Nature, Science, Proceedings of the National Academy of Sciences, and contributed to practical advances adopted by Google, Facebook, Amazon, Tesla and NVIDIA through dissemination of methods used in applications at Microsoft Azure, Amazon Web Services, Google Cloud Platform and Apple. The conference has fostered collaborations between laboratories such as DeepMind, OpenAI, MILA, Vector Institute and national research centers like CNRS, Max Planck Society and RIKEN, accelerating research in areas highlighted by awards like the Turing Award and leading to technologies implemented in products from IBM, Intel, Qualcomm and Samsung.

Category:Artificial intelligence conferences