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Real-Time Computation at the Edge of Chaos in Recurrent Neural Networks
2004
Neural Computation
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We analyze how the type of dynamics (ordered or chaotic) exhibited by randomly connected networks of threshold gates driven by a time varying input signal depends on the parameters describing the distribution ...
Hence, this result strongly supports conjectures that dynamical systems which are capable of doing complex computational tasks should operate near the edge of chaos, i.e. the transition from ordered to ...
Acknowledgments We would like to thank Alexander Kaske for stimulating discussions and helpful comments about the manuscript. ...
doi:10.1162/089976604323057443
pmid:15165396
fatcat:j6evksffgjaqnhshi7x2sp4qm4
Exploratory State Representation Learning
2022
Frontiers in Robotics and AI
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To solve the problems of exploration and SRL in parallel, we propose a new approach called XSRL (eXploratory State Representation Learning). ...
Not having access to compact and meaningful representations is known to significantly increase the complexity of reinforcement learning (RL). ...
The implementation details of the whole neural network are displayed in Table 3. γ = { , , FIGURE 1 . ...
doi:10.3389/frobt.2022.762051
pmid:35237669
pmcid:PMC8883277
fatcat:7h63vz56dfc25fyamsqofn5u4i
Review and Perspectives of Machine Learning Methods for Wind Turbine Fault Diagnosis
2021
Frontiers in Energy Research
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In the past decades, machine learning (ML) has showed a powerful capability in fault detection and diagnosis of WTs, thereby remarkably reducing equipment downtime and minimizing financial losses. ...
This study provides a comprehensive review of recent studies on ML methods and techniques for WT fault diagnosis. ...
and radial basis function (RBF) neural network. ...
doi:10.3389/fenrg.2021.751066
fatcat:bzniyxsgofh3pltcnrxd6avhbq
Artificial Intellgence – Application in Life Sciences and Beyond. The Upper Rhine Artificial Intelligence Symposium UR-AI 2021
[article]
2021
arXiv
pre-print
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, Offenburg and Trier, the Baden-Wuerttemberg Cooperative State University Loerrach, the French university network Alsace Tech (comprised of 14 'grandes \'ecoles' in the fields of engineering, architecture ...
and management) and the University of Applied Sciences and Arts Northwestern Switzerland. ...
(Charité, Institute of Pathology) for helpful comments and acknowledge the financial support by the Federal Ministry of Education and Research of Germany (BMBF) in the project deep.HEALTH (13FH770IX6). ...
arXiv:2112.05657v1
fatcat:wdjgymicyrfybg5zth2dc2i3ni
Artificial Intelligence in Cardiology: Present and Future
2020
Mayo Clinic proceedings
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Artificial intelligence (AI) is a nontechnical, popular term that refers to machine learning of various types but most often to deep neural networks. Cardiology is at the forefront of AI in medicine. ...
of findings, and addressing safety and ethical concerns before final implementation. ...
Schematic diagram of the development of a convolutional neural network. ...
doi:10.1016/j.mayocp.2020.01.038
pmid:32370835
fatcat:2g6tmuagd5ej7mz3jov4lrdj5i
Prospective Learning: Back to the Future
[article]
2022
arXiv
pre-print
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For example, an intelligence may see a set of pictures of objects, along with their names, and learn to name them. ...
, and engineer intelligences. ...
On the number of
linear regions of deep neural networks. ...
arXiv:2201.07372v1
fatcat:6qktqmoffvd4zl37ubd4wo2f2m
A Review of Some Techniques for Inclusion of Domain-Knowledge into Deep Neural Networks
[article]
2021
arXiv
pre-print
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This paper examines the inclusion of domain-knowledge by means of changes to: the input, the loss-function, and the architecture of deep networks. ...
We present a survey of ways in which existing scientific knowledge are included when constructing models with neural networks. ...
implemented by neural networks, and
set of rules. ...
arXiv:2107.10295v4
fatcat:ifkgq3cptbapfamr3dld57uruu
Situational Understanding in the Human and the Machine
2021
Frontiers in Systems Neuroscience
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Suggestions for further R&D are motivated by these hypotheses and are centered on the notions of Active Inference and Virtual Associative Networks. ...
We define situational understanding and the distinctions between understanding and awareness, consider examples of how understanding—or lack of it—manifest in performance, and review hypotheses concerning ...
Recent literature associates advanced cognitive capabilities in primates and humans with the ability to monitor the significance of multiple goals in parallel, and to switch between the goals (Mansouri ...
doi:10.3389/fnsys.2021.786252
pmid:35002643
pmcid:PMC8733725
fatcat:zeamg7i7rbc6rgh5ev7ffamx5a
Distributed Machine Learning in Materials that Couple Sensing, Actuation, Computation and Communication
[article]
2016
arXiv
pre-print
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, and corresponding training algorithms, to an amorphous network of computing nodes is considered. ...
Distributed versions of support vector machines, graphical models and mixture models developed in the field of wireless sensor networks are reviewed. ...
Artifical neural networks are common approaches to perform classification and regression in the literature cited [28, 29, 33, 36, 48, 84, 91, 92, 97, 113, 140, 142, 147, 149, 161, 162] . ...
arXiv:1606.03508v1
fatcat:zb5jcvda5jg6zpsv5w47wwr6nq
TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL
[article]
2021
arXiv
pre-print
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We open-source our environments, all studied ACL algorithms (collected from open-source code or re-implemented), and DRL students in a Python package available at https://github.com/flowersteam/TeachMyAgent ...
It includes 1) challenge-specific unit-tests using variants of a procedural Box2D bipedal walker environment, and 2) a new procedural Parkour environment combining most ACL challenges, making it ideal ...
Learning and development in neural networks:
the importance of starting small. Cognition, 48(1):71 -
99, 1993. ISSN 0010-0277.
Artif. Life, 25(4):352-365, 2019. ...
arXiv:2103.09815v2
fatcat:qtsp6ghsgrd47fwgznnqdwrtsu
Molecular Information Technology
2005
Critical reviews in solid state and materials sciences
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Investigations into qualitatively new concepts of information processing are underway in the areas of reaction-diffusion computing, self-assembly computing, and conformation-based computing. ...
Progress will depend on both novel computing concepts and innovations in materials. This article reviews current directions in the use of bulk and single molecules for information processing. ...
Cellular automata and neural networks provide possible starting points for parallel computing schemes more suitable to molecular implementation. ...
doi:10.1080/10408430590918387
fatcat:cg62axmewndhpdf2uo22knwvua
Automatic Curation of Court Documents: Anonymizing Personal Data
2022
Information
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The challenge was to find a good way of injecting specialized knowledge about person names syntax while taking profit of previous capabilities of pre-trained tools. ...
There are also interventions in the published data with the aim of generating metadata that enable a better experience of querying and navigation. ...
Cloze-driven Pretraining of Self-attention Networks. ...
doi:10.3390/info13010027
fatcat:ubnfktbvcfhtzl7rgndturoar4
The Tsetlin Machine – A Game Theoretic Bandit Driven Approach to Optimal Pattern Recognition with Propositional Logic
[article]
2021
arXiv
pre-print
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2020 pre-print arXiv:1804.01508v14 fatcat:pirfwuxxrbefndvldfg4ipv7jeOther Versions
Arguably, the Tsetlin Automaton is an even simpler and more versatile learning mechanism, capable of solving the multi-armed bandit problem. ...
In five benchmarks, the Tsetlin Machine provides competitive accuracy compared with SVMs, Decision Trees, Random Forests, Naive Bayes Classifier, Logistic Regression, and Neural Networks. ...
Code Availability Source code and datasets for the Tsetlin Machine, available under the MIT Licence, can be found at https://github.com/cair/TsetlinMachine and https://github.com/cair/pyTsetlinMachine. ...
arXiv:1804.01508v15
fatcat:ssmvlls2xfdjtbiagwxr5vq6hy
Digital Evolution for Ecology Research: A Review
2021
Frontiers in Ecology and Evolution
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This work has spanned a wide range of topics, including competition, facilitation, parasitism, predation, and macroecological scaling laws. ...
We argue for the value of further ecological research in digital evolution systems and present some particularly promising directions for further research. ...
The process of building the neural network from the genome mirrors development in nature (Channon and Damper, 2000). ...
doi:10.3389/fevo.2021.750779
fatcat:kcudtxl5yra7hpb2cjvz3zhlba
Evolution of functional specialization in a morphologically homogeneous robot
2009
Proceedings of the 11th Annual conference on Genetic and evolutionary computation - GECCO '09
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E. and J. C. Bongard. (2009). How robot morphology and training order affect the learning of multiple behaviors. ...
Particular focus is given to methods which evolve not only the control policies of manually-designed robots, but instead evolve both the control policy and physical form of the robot. ...
Due to the technical challenges of implementing a physical simulator, coupled with the lack of access to computing resources capable of comparable parallelization to the CM-5, it took several years before ...
doi:10.1145/1569901.1569915
dblp:conf/gecco/AuerbachB09
fatcat:pj7filcoufc7tb23ux3agpra5u
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