Paper Submission deadline: Friday May 14th

Due to many requests for an extension, the organizing committee has agreed to revisit the Paper Submission deadline until Friday May 14th.

Papers are pouring in and the organizing committee would like to thank all those who have already submitted papers. It is great to see the interest in ACAIN.
The ACAIN 2021 Program Committee will review all papers and abstracts and all submitters will receive information on whether their submission has been accepted by Friday July 30, 2021 the latest.
Those who have not submitted a paper yet are encouraged to do so here:

EasyChair

Please don’t hesitate to contact us if you need more information and/or details.

Hopefully see you, in 2D or 3D, in the Lake District in October!

Best regards,
ACAIN 2021 Organizing Committee.

Early Registration Deadline: Monday August 9th

The ACAIN 2021 Organizing Committee is pleased to announce that the Early Registration Deadline has been extended until Monday August 9th:

Deadlines

Those who have not Registered yet are encouraged to do so here:

Registration

Please don’t hesitate to contact us if you need more information and/or details.

Hopefully see you, in 2D or 3D, in the Lake District in October!
Best regards,
 ACAIN 2021 Organizing Committee.

ACAIN 2021: Co-located Event @ LOD 2021

On behalf of the Organizing Committee, we are proud to announce that the ACAIN 2021, will be a co-located event at LOD 2021.

The co-located event, ACAIN 2021, will be held in conjunction with LOD 2021.

So if  you register for LOD 2021 you will also be able to participate in ACAIN 2021 and vice versa.

The 7th Int. Conf. on Machine Learning, Optimization & Data Science – LOD 2021, October 5-8, 2021 – Grasmere, Lake District, England – UK

An Interdisciplinary Conference: Machine Learning, Optimization, Big Data & Artificial Intelligence without Borders

https://lod2021.icas.cc

lod@icas.cc

 

ACAIN 2021: an Online & Onsite Event!

After numerous discussions, we have concluded that holding the event this year in hybrid  form, both onsite and virtual  as this is most beneficial for the ACAIN community rather than postponing the conference to 2022.

The organizing committee of ACAIN 2021 has decided to run the advanced course and symposium  on the scheduled dates (October 5-8, 2021), and to run it as a hybrid event:

The Wordsworth Hotel & SPA  in Grasmere – Lake District England (our conference venue) has enough space to obey the safety rules (put in place due to COVID-19). To accommodate a large number of participants, we are offering the option for either physical presence (onsite) or virtual participation (online). We would be delighted if all authors and participants manage to attend; however, we are aware that in the current special circumstances, it is best to hold the event in hybrid mode.

The Advanced Course and Symposium, will be held in person with virtual rooms  for authors and participants using a remote connection (Zoom). The lectures  (e.g., live presentations or recorded ones) will also be made available online. We will make sure that the sessions also run live, such that the presenters can show and explain their results, and the attendees can ask questions and interact with the presenters. The sessions will be held one at a time which will allow participants from overseas to attend as many sessions as possible.

The keynote lectures will be recorded such that online participants can follow them either live or at any time they like to.

If the situation does not allow the event to take place in person, the event will instead be converted to a fully online mode.

Obviously, if ACAIN 2021 will be converted into a fully online event, participants who paid the onsite registration fee will be refunded the difference, and will thus only pay the online registration fee.

Finally, it is important to note that it is possible to change the mode of participation (the Registration):

from Onsite Registration to Online Registration and similarly

from Online Registration → to Onsite Registration

We are offering the possibility to change the mode of participation to ACAIN 2021. Those who register in one mode can easily change it by 5  September (one month before the event starts).

  • It is possible to take Onsite Registration and then change it to Online Registration and get a corresponding refund, but this decision must be made by 5  September.
  • Similarly, you can do Online Registration and then upgrade to Onsite Registration and pay the difference (via PayPal); this decision must also be made by 5  September.

If you have any questions please write to the organizing committee: acain@icas.cc

See you (in-person or virtually – in 3D or in 2D 🙂 ) in the Lake District – England  in October!

The ACAIN 2021 Organizing Committee.

It is possible to change the mode of participation (the Registration): from Onsite → to Online and similarly from Online → to Onsite (by 5 September)

It is possible to change the mode of participation (the Registration):

from Onsite Registration to Online Registration and similarly

from Online Registration  to Onsite Registration

We are offering the possibility to change the mode of participation to ACAIN 2021. Those who register in one mode can easily change it by 5 September (one month before the event starts).

  • It is possible to take Onsite Registration and then change it to Online Registration and get a corresponding refund, but this decision must be made by 5 September.
  • Similarly, you can do Online Registration and then upgrade to Onsite Registration and pay the difference (via PayPal); this decision must also be made by 5 September.

If you have any questions please write to the organising committee: acain@icas.cc

New Keynote Speaker: Timothy Lillicrap – DeepMind & UCL, UK

Timothy Lillicrap, Google DeepMind and UCL, UK

Timothy P. Lillicrap is a Canadian neuroscientist and AI researcher, adjunct professor at University College London, and staff research scientist at Google DeepMind, where he has been involved in the AlphaGo and AlphaZero projects mastering the games of Go, Chess and Shogi. His research focuses on machine learning and statistics for optimal control and decision making, as well as using these mathematical frameworks to understand how the brain learns. He has developed algorithms and approaches for exploiting deep neural networks in the context of reinforcement learning, and new recurrent memory architectures for one-shot learning.[1] His numerous contributions to the field have earned him a number of honors, including the Governor General’s Academic Medal, an NSERC Fellowship, the Centre for Neuroscience Studies Award for Excellence, and numerous European Research Council grants. He has also won a number of Social Learning tournaments.

https://en.wikipedia.org/wiki/Timothy_Lillicrap

https://scholar.google.co.uk/citations?user=htPVdRMAAAAJ&hl=en

https://contrastiveconvergence.net/~timothylillicrap/index.php

 

 

New Keynote Speaker: Prof. Maneesh Sahani, Gatsby Computational Neuroscience Unit, UCL, UK

Prof. Maneesh Sahani, Ph.D.
Professor of Theoretical Neuroscience and Machine Learning,
Director, Gatsby Computational Neuroscience Unit

Topics: Theoretical Neuroscience and  Machine Learning

Maneesh Sahani is Professor of Theoretical Neuroscience and Machine Learning at the Gatsby Computational Neuroscience Unit at University College London (UCL). Graduating with a B.S. in physics from Caltech, he stayed to earn his Ph.D. in the Computation and Neural Systems program, supervised by Richard Andersen and John Hopfield. After periods of postdoctoral work at the Gatsby Unit and the University of California, San Francisco, he returned to the faculty at Gatsby in 2004 and was elected to a personal chair at UCL in 2013. His work spans the interface of the fields of machine learning and neuroscience, with particular emphasis on the types of computation achieved within the sensory and motor cortical systems. He has helped to pioneer analytic methods which seek to characterize and visualize the dynamical computational processes that underlie the measured joint activity of populations of neurons. He has also worked on the link between the statistics of the environment and neural computation, machine-learning based signal processing, and neural implementations of Bayesian and approximate inference.

https://www.gatsby.ucl.ac.uk/~maneesh/