September 2022 - Comp-neuro - lists.cnsorg.org

Research Assistant Position in the Developmental Cognitive Neuroscience lab at American University, Washington DC

by Laurie Bayet

*Research Assistant Position in the Developmental Cognitive Neuroscience lab at American University, Washington DC* The Developmental Cognitive Neuroscience Laboratory at American University in Washington DC, directed by Dr. Laurie Bayet (https://www.bayetlab.com/ <https://urldefense.com/v3/__https://www.bayetlab.com/__;!!IaT_gp1N!17_aaQrx…>), is currently accepting applications for a full-time, benefits-eligible Research Assistant position, to assist on a 3-year NSF-funded project investigating infant visual cognition using electro-encephalography (EEG) and machine learning (NSF award # 2122961 <https://urldefense.com/v3/__https://www.nsf.gov/awardsearch/showAward?AWD_I…>). The position is ideal for an individual seeking to deepen their research experience in preparation for graduate study. *Apply at https://careers.american.edu/job-invite/10603/ <https://careers.american.edu/job-invite/10603/> and include a CV, cover letter, and names and contact information of 2-3 references.* Review of applications will begin immediately and continue until the position is filled. Prospective applicants may email Dr. Bayet (bayet(a)american.edu) with any questions. *Recent lab publications most relevant to the project:* Ashton, K., Zinszer, B. D., Cichy, R. M., Nelson, C. A., Aslin, R. N., & Bayet, L. (2022). Time-resolved multivariate pattern analysis of infant EEG data: A practical tutorial. *Developmental cognitive neuroscience*, *54*, 101094. https://doi.org/10.1016/j.dcn.2022.101094 <https://urldefense.com/v3/__https://doi.org/10.1016/j.dcn.2022.101094__;!!I…> Bayet, L., Zinszer, B. D., Reilly, E., Cataldo, J. K., Pruitt, Z., Cichy, R. M., Nelson, C. A., & Aslin, R. N. (2020). Temporal dynamics of visual representations in the infant brain. *Developmental cognitive neuroscience* , *45*, 100860. https://doi.org/10.1016/j.dcn.2020.100860 <https://urldefense.com/v3/__https://doi.org/10.1016/j.dcn.2020.100860__;!!I…> *Essential Functions:* 1. *Data Management:* Assisting with data collection in adherence with study protocols, such as: informed consent, EEG and eye-tracking measurements, transferring research data files to the lab server. 2. *Participant Recruitment and Support:* Outreach, recruitment, and communication with families who participate in the research, such as: designing and implementing outreach/recruitment materials, assessing study eligibility, scheduling study visits, maintaining contact with participating families. 3. *Data Entry and Processing:* Conduct data entry, data pre-processing, video coding, and data management, in adherence with study protocols. 4. *Personnel: *Onboarding and supervision of undergraduate research assistants. 5. *Study General Support:* Assisting with designing and implementing experimental procedures, such as: creating and validating stimuli, surveys, or paradigms; monitoring materials and supplies. 6. *Compliance:* Develop and monitor IRB protocols for approval, modification, or renewal. 7. *Other duties as assigned by supervisor:* Opportunity to contribute to conference presentations and/or manuscript writing, if desired. *Required Education and Experience:* - High School diploma or equivalent. - KSA Statement. - Interest in developmental psychology, cognitive science, and/or neuroscience. - Excellent organizational and project management skills, including Initiative, self-motivation, rigor, attention to details, ability to work independently on multiple tasks, learn new skills in a fast-paced environment, and meet deadlines. - Excellent communication and interpersonal skills, including comfort interacting professionally with families, infants, and undergraduate students; ability to work effectively with people from diverse backgrounds. - Prior experience in developmental research (e.g., with infants/children) and/or human neuroimaging research (e.g., EEG, MEG, fNIRS) (strongly preferred, but not strictly required if has some other relevant research experience). - Flexibility to adapt to changing hours, such as the ability to run study visits with families during weekends, or occasionally during the evening. *Preferred Education and Experience:* - Bachelor's degree in Psychology or Neuroscience or closely related field. - Computational skills and programming experience in Matlab, R, and/or Python preferred, but not strictly required. - Relevant experience with neuroscience/psychology research tools (e.g., NetStation, Psychtoolbox, Datavyu, Lookit, EEGLAB), data analysis, data processing, manuscript preparation, and/or social media/website development a plus. - The intention to make a 2-to-3-years commitment is preferred. The position currently has funding through August 2025, contingent upon a 6-month probationary period and successful completion of duties. *Additional information:* The Developmental Cognitive Neuroscience Laboratory is part of the Neuroscience Department <https://www.american.edu/cas/neuroscience/> and the Center for Neuroscience and Behavior <https://www.american.edu/cas/center-neuroscience/> at American University. American University provides a stimulating intellectual environment, just 2 miles from downtown Washington DC. DC offers a vibrant research community, and American University enjoys proximity to other notable research institutions such as the National Institutes of Health, Georgetown University, the University of Maryland, or Johns Hopkins University. With extensive public transit, an exciting cultural and restaurant scene, many museums and public parks, and proximity to other green spaces in the surrounding region (e.g., Appalachian trail, Shenandoah National Park), Washington DC consistently ranks amongst the top US metropolitan areas for quality of life. *Get to Know American University:* At American University we value open and honest inquiry, servant leadership, and the affirmation of the human dignity of all. We envision a thriving AU community where individuals of all identities and experiences are understood, appreciated, and fully included, and where equitable treatment, opportunities, and outcomes prevail. Our diverse community of students, faculty, and staff represent every state and more than 150 countries. Our internationally recognized faculty are today's thought leaders in the areas of public policy, law, the arts, communications, international development, and more. Our staff are innovative, service-oriented, and dedicated to moving the university towards achieving its strategic goals. We are committed to an excellent experience for all of our students, faculty and staff and share a passion for creating change through our knowledge and our work. Learn more about American University by clicking here <https://www.american.edu/about/au-at-a-glance.cfm>. *American University is an equal opportunity, affirmative action institution that operates in compliance with applicable laws and regulations. The university does not discriminate on the basis of race, color, national origin, religion, sex (including pregnancy), age, sexual orientation, disability, marital status, personal appearance, gender identity and expression, family responsibilities, political affiliation, source of income, veteran status, an individual’s genetic information or any other bases under federal or local laws (collectively "Protected Bases") in its programs and activities.* -- Laurie Bayet, PhD (hear name) <https://urldefense.com/v3/__https://namedrop.io/lauriebayet__;!!IaT_gp1N!17…> Assistant Professor of Neuroscience, American University (202) 885-1719

Sept. 17, 2022

3yr PhD / PostDoc position @ Ulm University

by Daniel Braun

There is a fully funded Phd or PostDoc level position available at the Institute of Neural Information Processing at Ulm University, Germany. At the institute we use a diverse set of methods to study the information processing principles underlying intelligent behavior in cognitive systems, including both biological and artificial systems. In particular, we are interested in systems that learn in open-ended environments and that use abstraction to solve novel problems through generalization and meta-learning. The applicants should have a strong mathematical background, hold a degree in natural science, mathematics, economics, psychology, computer science, engineering or similar and have a keen interest in artificial and natural intelligence. The positions are paid according to German tariff TVöD E13. Ulm University with its more than 10,000 students is Baden-Württemberg’s youngest university. It offers attractive career prospects in a highly innovative research, teaching and work environment at the same time facilitating the reconciliation of work and family life. The University of Ulm is an equal opportunity employer: Handicapped individuals are strongly encouraged to apply, and so are women in areas in which they are underrepresented. Knowledge of German is advantageous. The position is available from DEC 1, 2022 and will be filled as soon as possible. Candidates should submit a CV and a brief statement of interest through the university's online application system: stellenangebote.uni-ulm.de/jobposting/9c710d04684a751fcf4470b61d881631da41ddba -- Prof. Dr. Dr. Daniel Alexander Braun Institute of Neural Information Processing Faculty of Engineering, Computer Science and Psychology Ulm University James-Franck-Ring D-89081 Ulm Germany phone: +49 (0)731 50 - 24150 <%2B49%20%280%29731%2050%20-%2024158> fax: +49 (0)731 50 - 24156 email: daniel.braun(a)uni-ulm.de

Sept. 17, 2022

Tenure-track opening in Computational Social Science at UCLA

by Anne Warlaumont

Dear Colleagues, The University of California, Los Angeles (UCLA) Department of Communication invites applications for a tenure track appointment at the level of Assistant Professor with an emphasis on developing and/or applying computational social science methods to study communication. Potential areas of research include (but are by no means limited to) agent-based or other computational modeling, network science, machine learning, artificial intelligence, natural language processing, analysis of large audio and/or video datasets, gathering and analysis of digital trace data, and the use of virtual lab or field experiments. Interested candidates should view full posting and submit application materials via *UC Recruit here >>* <https://recruit.apo.ucla.edu/apply/JPF07843> Best regards, Anne

Sept. 15, 2022

General attendance open for Mathematics of Neuroscience Conference, Sept 24-25th 2022

by Ruairidh McLennan Battleday

Dear all, We now have a full schedule at this year's mathematics of neuroscience conference, in just under ten days (24-25th September, 2022), and have opened registration for virtual attendance: www.neuromonster.org We have tried to make the cost as low as possible, in the hope that everyone that wants to can come. It's a great line up, and we hope to see you there! All the best, Dr Ruairidh M. Battleday and Professor Dan V. Nicolau Jr

Sept. 14, 2022

Computational neuroscience - PhD/Postdoc - Cheng Lab, Bochum

by Vinita Samarasinghe

We (Cheng Lab <https://www.ini.rub.de/research/groups/computational_neuroscience/>, Ruhr University Bochum <https://rub.de/>, Germany) are looking to fill two positions in the area of computational neuroscience each for 3 years. _*Positions*_ 1. Postdoc: Join the team on project F01 <https://sfb1280.ruhr-uni-bochum.de/en/research/projects/f01/> of the Collaborative Research Center “Extinction Learning” SFB 1280 <https://sfb1280.ruhr-uni-bochum.de/en/home/> to: * analyze learning dynamics in behavioral, neural, and psychophysiological data, which will be collected by other projects within the SFB 1280. * compare the learning dynamics between individuals, species, learning phases and learning paradigms, * develop algorithms to analyze the learning dynamics, * develop and study computational models of learning dynamics, and * coordinate research with other participating projects. 2. PhD student or Postdoc: Develop and study computational models of episodic memory and spatial navigation by: * extending models based on large networks of biologically plausible spiking neurons with synaptic plasticity, * studying the generation and learning of complex spatial behaviors in the model, * quantitatively comparing the model output to the spatial behavior of mammals, and * studying the role of episodic memory in spatial navigation. The research groupis highly dynamic and uses diverse computationalmodeling approachesincludingbiological neural networks, cognitive modeling, and machine learning to investigatelearning and memory in humans and animals. _*Qualifications*_ * Adoctorate degreein neuroscience, physics, mathematics, electrical/biomedical engineering or a closely related field. In exceptional cases, graduate students with a Masters degree in these fields, but nodoctorate degree, may be considered. * Relevant experience in mathematical modeling together with a solid mathematics background * Relevant research experience in neuroscience or a related field (only position 1) * Be able to think algorithmically and have excellent programming skills (e.g., Python) * Excellent communication skills in English * Work well in a team. The Ruhr University Bochum is home to a vibrant research community in neuroscienceand cognitive science. The Institute for Neural Computation <https://www.ini.rub.de/> in the Faculty of Computer Science <https://informatik.rub.de/en/> combines different areas of expertise ranging from experimental and theoretical neuroscienceto machine learning androbotics. Please send your application, including CV, transcripts (bachelor & master) and research statement electronically, as a *single PDF* file, to samarasinghe(a)ini.rub.de <mailto:samarasinghe@ini.rub.de>. In addition, at least two academic references mustbe sent independently to the above email address. The Ruhr University Bochum is committed to equal opportunity. We strongly encourage applications from qualified women and persons with disabilities. We are committed to providing a supportive work environment for female researchers, in particular those with young children. Our university provides mentoring and coaching opportunities specifically aimed at women in research. We have a strong research network with female role models and will provide opportunities to networkwith them. Wherever possible, events will be scheduled during regular childcare hours. Special childcare will be arranged if events have to be scheduled outside of regular hours, in case of sickness and during school or daycare closures. Where childcare is not an option parents will be offered a home office solution. Contact person: Vinita Samarasinghe, samarasinghe(a)ini.rub.de <mailto:samarasinghe@ini.rub.de> -- Vinita Samarasinghe M.Sc., M.A. Science Manager Arbeitsgruppe Computational Neuroscience Institut für Neuroinformatik Ruhr-Universität Bochum, NB 3/73 Postfachnummer 110 Universitätstr. 150 44801 Bochum Tel: +49 (0) 234 32 27996 Email:samarasinghe@ini.rub.de

Sept. 12, 2022

PhD position in Neurotechnology at the Friedrich-Alexander-University (FAU) Erlangen-Nuremberg, Germany

by Reichenbach, Tobias

The Chair for Sensory Neuroengineering at the new Department Artificial Intelligence in Biomedical Engineering is looking for a PhD student to work on an innovative project in neurotechnology. Together with partners in the Cluster4Future SEMECO (TU Dresden, MED-EL, Fraunhofer) you will develop a Brain-Computer-Interface (BCI) for the next generation of hearing aids. To this end you will develop AI methods for analyzing brain signals and for steering the processing of acoustic signals. The prototype hearing aids with neurofeedback should be then be able to abadjust to the needs of their users and to adapt in real time. AI at the interface to neurobiology is a highly timely topic of immense societal relevance. We offer you the possibility to actively shape this exciting and rapidly developing field. We support your work through: - A lively scientific environment within the Department and the possibility to cooperate with excellent partners at the Friedrich-Alexander-University Erlangen-Nürnberg, at Imperial College London as well as with industry partners - An excellent environment to conduct leading science and to realise own scientific ideas - An excellent training in the development of AI methods for neuronal data - Development of your personal strengths, for instance through extensive courses on personal development - 26 days of holiday per year The renumeration is according to Group 13 of the German public service (TV-L). FAU is the most innovative university in Germany and ranks second among the most innovative European universities. It is located in one of the most attractive regions in Germany. Erlangen is a bicycle-friendly city with 100,000 inhabitants, former home of the Huguenots as well as a key location for industry. It is close to Nuremberg, a city with a population of half a million and a metropolitan flair. The mixture of academia, innovative companies, art and culture makes the region the perfect place for creative minds, keen athletes and nature lovers. To apply, please send a letter detailing your motivation, a CV, copies of your degrees and details of two referees. Please combine all documents into a single pdf and send them per email with subject “Application PhD student” to Prof. Dr. Tobias Reichenbach (tobias.j.reichenbach(at)fau.de<http://fau.de>). More information is available here: https://www.jobs.fau.de/jobs/phd-student-in-neurotechnology-u98170569/ ------------------------------------------- Prof. Dr. Tobias Reichenbach Chair of Sensory Neurotechnology Department Artificial Intelligence in Biomedical Engineering (AIBE) Friedrich-Alexander-University (FAU) Erlangen-Nürnberg Werner-von-Siemens-Strasse 61 91052 Erlangen https://www.neurotech.tf.fau.eu/

Sept. 10, 2022

Python Package: Echo State Networks

by Fabrizio Damicelli

Dear Computational Neuroscience Community, I would like to point you to a potentially useful Python Package that might be of interest for your research, especially in the realms of "Biologically-inspired Neural Networks", "Shallow Learning" and "Recurrent Neural Networks" in general. "echoes": Machine Learning with Echo State Networks, a scikit-learn compatible package. Code Repository: https://github.com/fabridamicelli/echoes A few interesting features: - scikit-learn compatible, i.e. scikit-learn tools such as GridSearchCV should work out-of-the-box - It is light-weight and fast (`numba` accelerated), i.e. many experiments can be simply run on a laptop - Flexible and customizable, e.g. use arbitrary connectivity, add custom activations, visualize neurons activity, etc. - Installation and getting started is easy: `pip install echoes` - Example notebooks: https://github.com/fabridamicelli/echoes/tree/master/examples/notebooks - Documentation: https://fabridamicelli.github.io/echoes/ As of today, a few people already trust it and the package registers >18K total downloads, ~500/month (pypi.org<http://pypi.org/>) and has been used already in a few research projects: - Hadaeghi et. al. (2021) Spatio-temporal feature learning with reservoir computing for T-cell segmentation in live-cell Ca2+ fluorescence microscopy: www.nature.com/articles/s41598-021-87607-y#Sec4<http://www.nature.com/articles/s41598-021-87607-y#Sec4> - Damicelli et.al<http://et.al/>. (2021) Brain Connectivity meets Reservoir Computing: www.biorxiv.org/content/10.1101/2021.01.22.427750v1.abstract<http://www.biorxiv.org/content/10.1101/2021.01.22.427750v1.abstract> - Fakhar et. al. (2022) Causal Influences Decouple From Their Underlying Network Structure In Echo State Networks: arxiv.org/abs/2205.11947<http://arxiv.org/abs/2205.11947> Check it out and any feedback/suggestions/bug reports are more than welcome (simply open an issue: https://github.com/fabridamicelli/echoes/issues) All the best, Fabrizio

Sept. 9, 2022

Postdoc / Junior Scientist / Research fellow positions in Complex Networks, Prague, Czech Republic

by Magda Pokorna

The following positions are open in the department of Complex Systems at the Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic. Applications for all positions will be reviewed on a rolling basis*with a first cut-off point on *30. **9**. 2022.** 1. *Postdoctoral / Junior Scientist position in Multimodal Neuroimaging Machine Learning, Prague, Czech Republic* A Postdoc or Junior Scientistposition is available to join the _Complex Networks and Brain Dynamics group <http://cobra.cs.cas.cz/>_for the project: /*“Predicting functional outcome in schizophrenia from multimodal neuroimaging and clinical data“*/funded by the Czech Health Research Council.The project involves the development of tools to predict the functional outcome of schizophrenia from multimodal neuroimaging, clinical and cognitive measurements taken early after disease onset. To overcome limitations due to high dimensionality of data, we combine robust machine-learning tools, data-driven feature selection and theory-based brain network priors. The project is carried out in collaboration with the National Institute of Mental Health, using its unique large rich imaging, cognitive and biochemical data of early stage schizophrenia patients. *For more information, conditions and application* see https://www.cs.cas.cz/job-offer/postdoctoral-junior-scientist-position-Hlin…. 2. *Researc**h Fellow / Postdoc positions in Complex Networks and Brain Dynamics, Prague, Czech Republic* We are looking for new team members to join the _Complex Networks and Brain Dynamics group <http://cobra.cs.cas.cz/>_to work on its interdisciplinary projects. The group is part of the Department of Complex Systems, Institute of Computer Science of the Czech Academy of Sciences - based in Prague, Czech Republic, _https://www.cs.cas.cz/ <https://www.cs.cas.cz/>_.We focus on the development and application of methods of analysis and modelling of real-world complex networked systems, with particular interest in the structure and dynamics of human brain function. Our main research areas are neuroimaging data analysis (fMRI & EEG, iEEG, anatomical and diffusion MRI), brain dynamics modelling, causality and information flow inference, nonlinearity and nonstationarity, graph theory, machine learning and multivariate statistics; with applications in neuroscience, climate research, economics and general communication networks. *More information about the group at *_*http://cobra.cs.cas.cz/* <http://cobra.cs.cas.cz/>_*. **For more information, conditions and application* see https://www.cs.cas.cz/job-offer/research-fellow-postdoc-position-Hlinka1-20…. *Do not hesitate to contact the **group leader**/ Principal Investigator for informal inquiries: Ing. Mgr. Jaroslav Hlinka, Ph.D. *_*hlinka[at]cs.cas.cz* <mailto:hlinka@cs.cas.cz>_*, *_*http://www.cs.cas.cz/hlinka/*_

Sept. 9, 2022

Postdoctoral Position at UConn in Systems and Computational Neuroscience

by Ian Stevenson

The Physiological Acoustics Lab (http://escabilab.uconn.edu) at the University of Connecticut seeks applicants for a postdoctoral position in systems and computational neuroscience. We are seeking highly motivated and creative applicants that can lead a project on perception and neural coding of speech and vocalizations in the presence of competing natural environmental noises (e.g., restaurant noise, busy street, construction noise etc.). The broad project goal is to study the neural basis for listening in noisy environments and to devise a general computational theory that accounts for perception and physiology. The project will use a variety of experimental approaches including human perception, awake animal electrophysiology, large scale neural recording, and computational modeling. UConn has a vibrant neuroscience community and there are opportunities for collaboration between departments and institutes. The primary appointment is in Biomedical Engineering, but the work will be conducted in collaboration with the Behavioral Neuroscience division in the Psychology department (Statistical Neuroscience Lab, http://stevenson.lab.uconn.edu; Sensory Perception and Neuroscience Lab, http://read.lab.uconn.edu) as well as Electrical and Computer Engineering and Biomedical Engineering. Qualifications: A PhD in Neuroscience, Biomedical Engineering, Electrical Engineering, Computational Neuroscience, or a related field is required. The ideal candidate will have an interdisciplinary research background in computational and systems neuroscience with prior research experience in awake animal neurophysiology. A strong analytic background in neural data analysis is desirable, particularly modeling neural systems and analyzing datasets from large-scale multi-channel neural recordings. Experience with acoustic signal processing, sound recognition, and machine learning is also desirable. Appointment: The position is funded through an R01 grant and salaries follow NIH post-doctoral scale and are based on experience. Applicants should email escabi(a)engr.uconn.edu a single PDF file containing: 1) resume including past research experience and published work 2) one page statement of prior research experience 3) one page statement of future research interests and objectives 4) names of at least two individuals who can provide reference letters Ian Stevenson Associate Professor University of Connecticut Department of Psychological Sciences stevenson.lab.uconn.edu

Sept. 8, 2022

Job: ML Engineer to extend ReservoirPy library for health data (Reservoir Computing)

by Xavier Hinaut

We are looking for an engineer for at least one year to work with the open source ReservoirPy library on health data. You will be working in Bordeaux, France in the Mnemosyne computational neuroscience group https://team.inria.fr/mnemosyne <https://team.inria.fr/mnemosyne> in collaboration with other Bordeaux teams involved in biostatistics and machine learning. More info and online application: https://jobs.inria.fr/public/classic/en/offres <https://jobs.inria.fr/public/classic/en/offres> * ReservoirPy ReservoirPy [1, 2, 3] is a simple user-friendly library based on Python scientific modules. It provides a flexible interface to implement efficient Reservoir Computing (RC) [5] architectures with a particular focus on Echo State Networks (ESN) [4]. Advanced features of ReservoirPy allow to improve computation time efficiency on a simple laptop compared to basic Python implementation. Some of its features are: offline and online training, parallel implementation, sparse matrix computation, fast spectral initialization, advanced learning rules (e.g. Intrinsic Plasticity) etc. It also makes possible to easily create complex architectures with multiple reservoirs (e.g. deep reservoirs), readouts, and complex feedback loops. Moreover, graphical tools are included to easily explore hyperparameters with the help of the hyperopt library. It includes several tutorials exploring exotic architectures and examples of scientific papers reproduction. Github: https://github.com/reservoirpy/reservoirpy <https://github.com/reservoirpy/reservoirpy> Documentation: https://reservoirpy.readthedocs.io <https://reservoirpy.readthedocs.io/> Related projects: https://github.com/reservoirpy <https://github.com/reservoirpy> Twitter: https://twitter.com/reservoirpy <https://twitter.com/reservoirpy> * Deadline: 20th of September 2022 For informal questions send an email to xavier dot hinaut at inria dot fr. Online application: https://jobs.inria.fr/public/classic/en/offres <https://jobs.inria.fr/public/classic/en/offres> * Contract Engineer contract of 1 year, with possibility to extend the contract to more years or to continue in the team as PhD student. * Benefits package - Subsidized meals - Partial reimbursement of public transport costs - Possibility of partial teleworking and flexible organization of working hours - Professional equipment available (videoconferencing, loan of computer equipment, etc.) - Social, cultural and sports events and activities - Access to vocational training - Social security coverage [1] Trouvain N, Pedrelli L, Dinh TT, Hinaut X (2020). Reservoirpy: an efficient and user-friendly library to design echo state networks. International Conference on Artificial Neural Networks, 494-505. https://hal.inria.fr/hal-02595026v2/document <https://hal.inria.fr/hal-02595026v2/document> [2] Trouvain, N., Rougier, N. P., & Hinaut, X. (2022). Create Efficient and Complex Reservoir Computing Architectures with ReservoirPy. In FROM ANIMALS TO ANIMATS 16: The 16th International Conference on the Simulation of Adaptive Behavior (SAB2022). https://hal.inria.fr/hal-03761440/document <https://hal.inria.fr/hal-03761440/document> [3] Nathan Trouvain, Xavier Hinaut. reservoirpy: A Simple and Flexible Reservoir Computing Tool in Python. 2022. HAL preprint hal-03699931. https://hal.inria.fr/hal-03699931/document <https://hal.inria.fr/hal-03699931/document> [4] Jaeger, H., & Haas, H. (2004). Harnessing nonlinearity: Predicting chaotic systems and saving energy in wireless communication. science, 304(5667), 78-80. [5] Lukoševičius, M., & Jaeger, H. (2009). Reservoir computing approaches to recurrent neural network training. Computer Science Review, 3(3), 127-149. Xavier Hinaut Inria Research Scientist www.xavierhinaut.com -- +33 5 33 51 48 01 Mnemosyne team, Inria, Bordeaux, France -- https://team.inria.fr/mnemosyne & LaBRI, Bordeaux University -- https://www4.labri.fr/en/formal-methods-and-models & IMN (Neurodegeneratives Diseases Institute) -- http://www.imn-bordeaux.org/en --- Our Reservoir Computing library: https://github.com/reservoirpy/reservoirpy

Sept. 6, 2022