Andreas (Andrzej) Wichert
Associated Professor with Habilitation
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ORCID ,
AMS profile ,
Google Scholar , ResearchGate ,
dblp ,
amazon
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Univesidade de Lisboa / INESC-ID
Campus IST-Taguspark / Avenida Professor Cavaco Silva
2744-016 Porto Salvo, Portugal
Email: andreas.wichert at tecnico.ulisboa.pt
Telephone: +351 214233231, Office: 2N-5.7
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Born in Poland, Wroclaw. His grandfather Wladyslaw Wichert was a Polish officer.
He studied computer science at the University of Saarland, where he graduated in 1993. Afterwards, he became a PhD student at the Department of Neural Information Processing, University of Ulm. During this period he worked at the DaimlerChrysler Research and Technology Speech Recognition Group. He received a PhD in computer science in 2000 with his work on associative computation. He has since worked in the field of fMRI as a researcher with an interdisciplinary group, Department of Psychiatry III Ulm, changing to F&K Delvotec bonding machines where he led the development of a diagnostic expert system. From 2004 to 2005 he was the scientific director of MITI research group Klinikum rechts der Isar of the Technical University Munich. Since 2006, he is a researcher of INESC-ID.
Since 2009 he is a member of the Group of AI for People and Society (gaips).
His research focuses on Artificial Intelligencei, Machine Learning, Neural Networks, Quantum Cognition, Quantum Artificial Intelligence.
Series Editor
Chapman & Hall/CRC Quantum Computing Series
Recent Books
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Quantum Artificial Intelligence with Qiskit
Introducing symbolical quantum algorithms, sub symbolical quantum algorithms and quantum Machine Learning (ML) algorithms, this book explains each process step-by-step with associated QISKIT listings.
All examples are additionally available for download at GitHub
(supports qiskit 0.x and 1.x)
Please email me corrections, suggestions or comments!
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Mind, Brain, Quantum AI, and the Multiverse
Indicates how we can provide an answer to the problem of the mind and consciousness by describing the nature of the physical world,
proposed explanation includes the Everett Many-Worlds theory.
Essential compilation of knowledge in philosophy, computer science, biology, and quantum physics. It is written for readers without any requirements in mathematics, physics, or computer science.
Please email me corrections, suggestions or comments!
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Machine Learning - A Journey to Deep Learning
with Exercises and Answers
Learning from three different perspectives - the statistical perspective, the artificial neural network perspective and the deep learning methodology
Tells a story outgoing from a perceptron to deep learning highlighted with concrete examples, including exercises and answers for the students
Machine Learning Slides
Please email me corrections, suggestions or comments!
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Principles of Quantum Artificial Intelligence: Quantum Problem Solving and Machine Learning, 2nd Edition
Most of the chapters were rewritten and extensive new materials were updated
New topics include quantum machine learning, quantum-like Bayesian networks and mind in Everett many-worlds
Please email me corrections, suggestions or comments!
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Intelligent Big Multimedia Databases
Multimedia databases are categorized into many major areas
This book unifies the essential concepts and recent algorithms into a single comprehensive volume
Please email me corrections, suggestions or comments!
Errata
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Recent Publications
Joaquim Mussandi, Andreas Wichert, NLP Tools for African Languages: Overview, Proceedings of the 16th International Conference on Computational Processing of Portuguese-Vol. 2, 2024
Maria Osorio and Andreas Wichert, Promoting the Shift from Pixel-Level Correlations to Object Semantics Learning by Rethinking Computer Vision Benchmark Datasets, Neural Computation, 36(8) : 1626-1642, 2024 doi:10.1162/neco_a_01677
Maria Osorio and Luis Sa-Couto and Andreas Wichert. Can a Hebbian-like learning rule be avoiding the curse of dimensionality in sparse distributed data?, Biological Cybernetics, 2024 doi:10.1007/s00422-024-00995-y
Andreas Wichert, Quantum Machine Learning - Quo Vadis?, Entropy, 26(11), 905, 2024 doi:10.3390/e26110905
Publications
Projects
HEIDI (HEIGH Dimensional Indexing) or how to index one billion of vectors
Lectures (.. in the majority of cases you can download the slides at the menue point Teoricas)
[L1]
Artificial Intelligence 96/97, 97/98,
15/16,
18/19
[L2] Telemedicine 03/04, 04/05
[L3] Decision Support Systems
A-05/06,
T-05/06,
06/07,
07/08,
08/09,
09/10,
10/11,
11/12,
13/14,
14/15,
15/16,
16/17,
17/18
[L4] Intelligent Multimedia Databases:
06/07,
07/08,
08/09,
09/10
10/11,
11/12,
13/14,
14/15
[L5] Algorithms: 06/07, 07/08, 08/09
[L6] Information and Computation for AI:
07/08,
09/10,
10/11,
11/12,
13/14,
14/15
[L7] Symbolical and Subsymbolical learning
08/09,
09/10,
11/12,
13/14,
14/15,
15/16,
16/17
18/19
19/20
20/21
21/22
22/23
23/24
[L8] Logic for Programming
17/18
24/25
[L9] Machine Learning
18/19
19/20
20/21
21/22
22/23
23/24
24/25
[L10] Deep Learning
21/22
22/23
23/24
Excellence result in teaching for Machine Learning 21/22, 23/24
Decision Support Systems 14/15 and Intelligent Multimedia Databases and 14/15
Manual
R for Data Science
PhD Student
Maria Osorio
Jose Miguel Penedo Ramos
Joaquim Domingos Mussandi
PhD Students (past)
Dr. Luis Tarrataca
Dr. Angelo Cardoso
Dr. Joao Sacramento
Dr. Catarina Pinto Moreira
Dr. Luis Sa-Couto
Personal,
Facebook
Catalogue: Holy Pictures of Another Time
Procreate: Portfolio
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