Dr Mehmet Suzen MInstP Theoretical Physicist | Research Scientist

Publications: Recent and Selected

• Gibbs randomness-compression proposition: An efficient deep learning
  arXiv:2505.23869 (2025)
  Code and data repository
  
  
• Understanding entropy production with a thermal zero-player game
  arXiv preprint arXiv:2503.03769 (2025) | code and data repository
  
  
• In-context learning as a new kind of symbolic-AutoML: Lyapunov conjecture for CoTs.
  HAL Science (2024)
  
  
• H-theorem do-conjecture
  arXix:2310.01458 (2023) | Code-repo
  
  
• Cooperative Phenomenon: Statistical Physics Origins of Connectionist Learning
  hal-03650339 (2022)
  


• Empirical deviations of semicircle law in mixed-matrix ensembles
  hal-03464130 (2021) | notebook
  


• Equivalence in Deep Neural Networks via Conjugate Matrix Ensembles
  arXiv:2006.13687 | deep_dyson_networks.ipynb
  
  
• Compressive transition path sampling: How to simulate rare event for longer time scales?
  Manuscript: arXiv:1804.09781
  
  
• How can we test that gravity is an entropic force?
  A testable prediction from entropic gravity
  arXiv:1612.00288


• Effective ergodicity in single-spin-flip dynamics
  Phys. Rev. E 90, 032141 (2014) DOI: 10.1103/PhysRevE.90.032141
  Mehmet Suezen
  

Thesis

• Induced Charge Computation, Ph.D. Dissertation, Frankfurt Main
  
• Chaotic behaviour of geodesics, MSc Thesis in Theoretical Physics, Cyprus

Blog Posts: Selected and Recent

• Ultimate physical limit of data storage: Connecting Bekenstein Bound to Landauer Principle (April 2025)
• Numerical stability showcase: Ranking with SoftMax or Boltzmann factor (April 2025)
• Basic understanding of a metric tensor: Disassemble the concept of a distance over Riemannian Manifolds (April, 2024))
• Practical causal ordering: Why weighted-Directed Acyclic Graphs (DAGs) are powerful for causal inference? (September 2023)
• Bayesian rabbit holes: Decoding conditional probability with non-commutative algebra (July 2022)
• Empirical risk minimization is not learning : A mathematical definition of learning and re-understanding of overfitting and Occam's razor in machine learning (June 2022)
• A misconception in ergodicity: Identify ergodic regime not ergodic process. (May 2022)
• Physics origins of the most important statistical ideas of recent times (January 2022)
• Deep Learning in Mind a Gentle Introduction to Spectral Ergodicity (July 2021)
• A New Matrix Mathematics for Deep Learning : Random Matrix Theory of Deep Learning (July 2021)
• Full cross-validation and generating learning curves for time-series models (June 2021)
• On the fallacy of replacing physical laws with machine learned inference systems. (April 2021)
• Statistical Physics Origins of Connectionist Learning: Cooperative Phenomenon to Ising-Lenz Architectures. (December 2020)
• A practical understanding of ergodicity (January 2020)
• Bringing back the Occam's razor to modern connectionist machine learning. (December 2019)
• On modern data scientist: A blind empiricist is not a data scientist (September 2019)
• Research as a core driver in AI and Data Science (January 2019)
• Understanding overfitting: an inaccurate meme in supervised learning (August 2017)
• Pitfalls in pseudo-random number sampling at scale with Apache Spark (July 2017)
• Practical Kullback-Leibler (KL) Divergence: Discrete Case (January 2017)
• Economy and dynamic modelling: Haavelmo's approach (July 2016)
• S-shaped data: Smoothing with quasibinomial distribution (January 2016)
• Testing emergent gravity: Gravitational Lensing to atom interferometer (January 2017)
• Understanding the empirical law of large numbers and the gambler's fallacy (August 2016)
• Is ergodicity a reasonable hypothesis? Understanding Boltzmann's ergodic hypothesis (May 2014)
• N-body wave function has no meaning but shut up and calculate: quantum bayesianism (June 2013)

Datasets

• Migrating birds real flight V-formation spatial configuration.
  zenodo (2021).
• Effective ergodicity in single-spin-flip dynamics
  zenodo (2017).

Supervisions and mentoring service to community

• Mentor Data Scientists and engineers: Machine learning and data mining projects.
• Mentor/provide guidance to academic colleagues.
• Supervise academic theses in computer science and theoretical physics.

Music

• Bruce Dickinson was kind enough to play my request on BBC

Compositions

• Othello Suite Castle I : Intro Score pdf | Midi in mp3

(c) 2016-2025 by Mehmet Suezen
mehmet.suzen at physics dot org
All rights reserved
Do not copy or distribute without prior permission.
Live long and prosper in peace
In memory of Leonard Nimoy

.Liberté.Égalité.Fraternité.