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Advances in Cognitive Neurodynamics (VII)
This book contains original articles submitted to the Seventh International Conference on Cognitive Neurodynamics (ICCN 2019). The brain is an endless case study of a complex system characterized by multiple levels of integration, multiple time scales of activity, and multiple coding and decoding properties. The contribution of several disciplines, mathematics, physics, computer science, neurobiology, pharmacology, physiology, and behavioral and clinical sciences, is necessary in order to cope with such seemingly unattainable complexity that transforms the experimental information into a tricky puzzle which hides the correspondence with model predictions. This conference gathered active participants to discuss ideas and pose new questions from different viewpoints, ranging from single neurons and neural networks to animal/human behavior in theoretical and experimental studies. The conference is organized with plenary lectures, mini-symposia, interdisciplinary round tables, and oral and poster sessions.
Decision Making with Imperfect Decision Makers
Prescriptive Bayesian decision making has reached a high level of maturity and is well-supported algorithmically. However, experimental data shows that real decision makers choose such Bayes-optimal decisions surprisingly infrequently, often making decisions that are badly sub-optimal. So prevalent is such imperfect decision-making that it should be accepted as an inherent feature of real decision makers living within interacting societies. To date such societies have been investigated from an economic and gametheoretic perspective, and even to a degree from a physics perspective. However, little research has been done from the perspective of computer science and associated disciplines like ...
Artificial Neural Networks and Machine Learning – ICANN 2023
The 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023. The 426 full papers, 9 short papers and 9 abstract papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications.
AI in Drug Discovery
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Artificial Neural Networks and Machine Learning – ICANN 2022
The 4-volumes set of LNCS 13529, 13530, 13531, and 13532 constitutes the proceedings of the 31st International Conference on Artificial Neural Networks, ICANN 2022, held in Bristol, UK, in September 2022. The total of 255 full papers presented in these proceedings was carefully reviewed and selected from 561 submissions. ICANN 2022 is a dual-track conference featuring tracks in brain inspired computing and machine learning and artificial neural networks, with strong cross-disciplinary interactions and applications. Chapter “Sim-to-Real Neural Learning with Domain Randomisation for Humanoid Robot Grasping ” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Artificial Neural Networks and Machine Learning – ICANN 2019: Deep Learning
The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions.
Advances in Cognitive Neurodynamics (V)
This proceedings contains articles submitted to the fifth International Conference on Cognitive Neurodynamics (ICCN2015). In ICCN2015, twelve invited plenary lectures were presented by the leading scientists in their respective research fields. More than 15 mini-symposiums are organized by specialists with topics covering: motor control and learning, dynamic coding in distributed neural circuits, dynamics of firing patterns and synchronization in neuronal systems, information and signal processing techniques in neurotechnology, neural oscillations and synaptic plasticity in the hippocampus, new perspective on model-based vs. model-free brain process, neural mechanisms of internal switching, neuroinformation computation, neural model and dynamics, imaging human cognitive networks, neuroinformatics, neuroergonomics & neuroengineering, dynamic brain for communication, visual information processing and functional imaging and neural mechanisms of language processing. All articles are peer-reviewed. The ICCN is a series conference held every two years since 2007.
Decision Making and Imperfection
Decision making (DM) is ubiquitous in both natural and artificial systems. The decisions made often differ from those recommended by the axiomatically well-grounded normative Bayesian decision theory, in a large part due to limited cognitive and computational resources of decision makers (either artificial units or humans). This state of a airs is often described by saying that decision makers are imperfect and exhibit bounded rationality. The neglected influence of emotional state and personality traits is an additional reason why normative theory fails to model human DM process. The book is a joint effort of the top researchers from different disciplines to identify sources of imperfection...
Artificial Neural Networks and Machine Learning -- ICANN 2012
The two-volume set LNCS 7552 + 7553 constitutes the proceedings of the 22nd International Conference on Artificial Neural Networks, ICANN 2012, held in Lausanne, Switzerland, in September 2012. The 162 papers included in the proceedings were carefully reviewed and selected from 247 submissions. They are organized in topical sections named: theoretical neural computation; information and optimization; from neurons to neuromorphism; spiking dynamics; from single neurons to networks; complex firing patterns; movement and motion; from sensation to perception; object and face recognition; reinforcement learning; bayesian and echo state networks; recurrent neural networks and reservoir computing; coding architectures; interacting with the brain; swarm intelligence and decision-making; mulitlayer perceptrons and kernel networks; training and learning; inference and recognition; support vector machines; self-organizing maps and clustering; clustering, mining and exploratory analysis; bioinformatics; and time weries and forecasting.
