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Complexity Research Team (CRT)

"Chaos is the beginning, simplicity is the end.", M.C. Escher

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Month: November 2020

Professor Robert Sapolsky: “Chaos and Reductionism”

Posted on 25/11/202008/03/2022 by karaka
Posted in Chaos, Educational Tutorials, Physics Tagged Chaos, Reductionism, Robert Sapolsky, Stanford University

Professor Constantino Tsallis “Knowledge and Uncertainty in Physics – Foundations and Applications”

Posted on 25/11/202008/03/2022 by karaka
Posted in Educational Tutorials, Physics, Tsallis q-extensive statistics Tagged Constantino Tsallis, EBICC 2017

Professor Georgios Pavlos: “Complexity and Unification in Physical Theory”

Posted on 19/11/202008/03/2022 by karaka
Posted in Chaos, Educational Tutorials, Physics, Tsallis q-extensive statistics Tagged Complexity, Georgios Pavlos, Physical Theory, Unification

Machine learning analysis of chaos and vice versa

Posted on 12/11/202008/03/2022 by karaka
Posted in Chaos, Educational Tutorials, Machine Learning, Physics Tagged Chaos, Dynamical Systems, Machine Learning

Neural Networks – Deep Learning

Posted on 12/11/202008/03/2022 by karaka
Posted in Deep Learning, Educational Tutorials, Neural Networks

Complexity Theory Courses

Posted on 12/11/202008/03/2022 by karaka
Posted in Educational Tutorials, Physics

Complexity theory, time series analysis and Tsallis q-entropy principle part one: theoretical aspects

Posted on 12/11/202008/03/2022 by karaka

https://www.degruyter.com/downloadpdf/journals/jmbm/26/5-6/article-p139.xml

Posted in Physics, Tsallis q-extensive statistics Tagged Complexity theory, timeseries analysis, Tsallis q-entropy principle

(PINNs) – Physics Informed Neural Networks: Algorithms, Theory, and Applications

Posted on 11/11/202008/03/2022 by karaka
Posted in Machine Learning, Physics Tagged Machine Learning, Neural Networks, Physics

Recent Posts

  • Spatial constrains and information content of sub-genomic regions of the human genome 11/09/2022
  • Special Issue “Coexistence of Complexity Metrics and Machine-Learning Approaches for Understanding Complex Biological Phenomena” 15/12/2020
  • Professor Robert Sapolsky: “Chaos and Reductionism” 25/11/2020

RSS Machine Learning

  • Looking beyond natural sequences 27/08/2026
    A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.
    Lillian Eden | Department of Biology
  • AI helps design new materials that work in the real world 26/08/2026
    The “CrysVCD” tool developed at MIT could cut the huge amounts of time and money spent on screening out chemically unstable designs.
    Zach Winn | MIT News
  • Generating scenarios for extreme events, without extreme data 24/08/2026
    A new algorithm learns to anticipate the unprecedented scenarios that critical infrastructure and global supply chains are least prepared for.
    Jennifer Chu | MIT News

RSS Biology and Genetics

  • Looking beyond natural sequences 27/08/2026
    A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.
    Lillian Eden | Department of Biology
  • Cells use a little-known molecule to protect themselves from iron overload 25/08/2026
    This discovery points toward new combination strategies against cancer, and may explain the iron buildup seen in disorders such as early-onset Parkinson’s disease.
    Shafaq Zia | Whitehead Institute
  • How the Toxoplasma parasite adapts to crowded conditions in host cells 19/08/2026
    A new study by Whitehead Institute researchers identifies how the widespread parasite Toxoplasma gondii survives in crowded environments in infected cells, which helps it persist in long-lasting brain cysts.
    Mackenzie White | Whitehead Institute

Machine Learning Mastery

  • Learn Vectorized Thinking in Python Through Examples
  • Comparing Local Tool Calling: Gemma 4 vs. Llama 3 vs. Mistral
  • Integrating Agentic AI with Existing Machine Learning Pipelines
  • How to Build a Robust RAG System with Minimal Resources
  • Managing Small Context Windows in Language Models

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