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Artificial neural network modelling - volume 628

Advances in Self-Organizing Maps and Learning Vector Quantization: Proceedings of the 11th International Workshop WSOM 2016, Houston, Texas, USA, January 6-8, 2016 - 428

Neural Information Processing: Research and Development - 152

Coherent Structures in Complex Systems: Selected Papers of the XVII Sitges Conference on Statistical Mechanics. Held at Sitges, Barcelona, Spain, 5-9 June 2000. Preliminary Version - 567

Neural Networks Theory

Knowledge-based neurocomputing: a fuzzy logic approach - v. 234

Fuzzy rationality: a critique and methodological unity of classical, bounded and other rationalities - v. 235

Epistemic foundations of fuzziness: unified theories on decision-choice processes - v. 236

Fuzziness and approximate reasoning: epistemics on uncertainty, expectation and risk in rational behavior - v. 237

Neural networks: computational models and applications - v. 53

Speech, audio, image and biomedical signal processing using neural networks

Models of Neural Networks IV: Early Vision and Attention

The making of a neuromorphic visual system

FPGA implementations of neural networks

Intelligent Networks and Intelligence in Networks: IFIP TC6 WG6.7 International Conference on Intelligent Networks and Intelligence in Networks, 2-5 September 1997, Paris, France

Handbook of neural computation

Deep neural network applications

Deep Neural Network Applications

Toward deep neural networks: WASD neuronet models, algorithms, and applications

Toward deep neural networks: WASD neuronet models, algorithms, and applications

Untangling complex systems: a grand challenge for science

Untangling Complex Systems: A Grand Challenge for Science

Interpretable Machine Learning With Python: Build Explainable, Fair, and Robust High-Performance Models With Hands-on, Real-World Examples

Evolving connectionist systems: the knowledge engineering approach

Learning with recurrent neural networks - 254

Deep learning with MXNet cookbook: deep dive into a variety of recipes to build, train, and deploy scalable AI models on Apache MXNet

Neural networks with Keras cookbook: over 70 recipes leveraging deep learning techniques across image, text, audio, and game bots.

Hands-On Machine Learning for Algorithmic Trading: Design and implement investment strategies based on smart algorithms that learn from data using Python

Hands-On Generative Adversarial Networks with PyTorch 1.x: Implement next-generation neural networks to build powerful GAN models using Python

TensorFlow 2.0 Quick Start Guide: Get up to speed with the newly introduced features of TensorFlow 2.0

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