notes

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index

)
  • Aristotle
  • Gottfried Leibniz
  • John Dewey
  • statistical physics
  • philosophy
  • open documents
  • open data sets
  • maxima
  • Making presentations in org-mode
  • linear models
  • a containerized jupyter notebook with multiple kernels on Arch Linux
  • Towards A Principled Bayesian Workflow by Michael Betancourt in 2020
  • Connect emacs TRAMP to gcp container using gcloud compute config-ssh
  • Non-equilibrium statistical physics
  • Data analysis using regression and multilevel hierarchical models by Andrew Gelman and Jennifer Hill in 2006
  • Bayesian data analysis by Andrew Gelman, Aki Vehtari, et al in 2014
  • Approximation and solution methods for master equations
  • Applied Probabilistic Modeling Principled Bayesian Inference for the Discerning Practitioner by Michael Betancourt in 2020
  • A kinetic view of statistical physics by Pavel Krapivsky, Sidney Redner, and Eli Ben-Naim in 2010
  • Decent espresso
  • converting jupyter notebooks to org mode
  • Chaining maxima blocks in org mode
  • Analytic and numerical investigation of stochastic processes
  • video editing
  • tiling window managers
  • spinors
  • service mesh
  • probcomp hosted jupyter hub
  • pathology references
  • kubernetes on gke with terraform
  • jupyter hub
  • interacting particle systems
  • fibration
  • digital physics
  • conformal field theory
  • computation
  • approximate bayesian computation
  • Physics and geometry by Edward Witten in 1986
  • Experiential learning by David Kolb in 2015
  • Dynamic causal modelling of COVID-19 by Karl Friston, Thomas Parr, Jean Daunizeau, Rosalyn Moran, et al in 2020
  • An approximation to an efficient fundamental physics curriculum
  • A thorough introduction to the theory of general relativity by Frederic Schuller in 2015
  • A Visual Introduction to Differential Forms and Calculus on Manifolds by Fortney in 2018
  • video streaming
  • Removing private files from the hugo posts folder
  • Managing org-roam for public and private collaboration
  • reading list
  • the roadmap for web development
  • research
  • news
  • Didier Debaise
  • stochastic processes
  • Why you should walk more by Kelly Starrett in 2020
  • What kind of explanation qualifies as a causal theory of the origin of a biosphere?
  • Wall street week
  • Universality in intermediary metabolism by Eric Smith and Harold Morowitz in 2004
  • The Origin and Nature of Life on Earth The emergence of the fourth geosphere by Eric Smith and Harold Morowitz in 2016
  • The Molecular Basis of Cancer by John Mendelsohn et al in 2014
  • The information geometry of 2-field functional integrals by Eric Smith in 2019
  • The Bayesian brain the role of uncertainty in neural coding and computation by David C.Knill and Alexandre Pouget in 2004
  • Steven Levine
  • screencasting
  • scientific collaboration
  • roam
  • Reza Negarestani
  • Population Extinction on a Random Fitness Seascape by Bertrand Ottino-Loffler and Mehran Kardar in 2020
  • molecular pathology
  • Middlesex Fells Reservation
  • Probabilistic Modeling and Statistical Inference by Michael Betancourt in 2019
  • Martin Biehl
  • Henry's Clinical diagnosis and management by McPherson and Pincus in 2016
  • Growth dynamics in naturally progressing chronic lymphocytic leukaemia by Michaela Gruber, Gad Getz, and Catherine Wu in 2020
  • flow cytometry
  • Easy and hard in the origin of life by Eric Smith in 2019
  • Eric Smith The Origin and Nature of Life on Earth on The Dissenter by Ricardo Lopes April 23, 2018
  • coffee
  • Biology of information lectures at College de France
  • Billions
  • Bayesian probabilistic inference for stochastic processes
  • Bayesian informal logic and fallacy by Kevin Korb in 2003
  • Bayesian approaches to clinical trials and health-care evaluation by David Spiegelhalter, Keith Abrams, and Jonathan Myles in 2004
  • Applications of probabilistic inference to the interpretation of simple experiments
  • Aki Vehtari
  • A statistical approach for tracking clonal dynamics in cancer using longitudinal next-generation sequencing data by Dimitrios Vavoulis et al in 2020
  • Physics from Symmetry by Jakob Schwichtenberg in 2015
  • Nicholas Rescher
  • The 2010s Our Decade of Deep Learning Outlook on the 2020s by Jürgen Schmidhuber in 2020
  • free energy principle
  • Facets of Systems Science 2nd ed by George Klir in 2001
  • Principles of the self-organizing system by W. Ross Ashby in 1962
  • use kubernetes on gke with terraform to deploy jupyter hub
  • The free energy principle for action and perception A mathematical review by Christopher Buckley, Anil Seth, et al in 2017
  • system-environment distinction
  • single-cell transcriptome analysis
  • population dynamics
  • physiological timescale
  • physics
  • Russ Salakhutdinov's lectures on Large Scale Machine Learning
  • probabilistic inference
  • variational inference
  • How does monad-bayes compare to pyro?
  • How can one setup an inexpensive gke kubernetes cluster with no load balancer using terraform running jupyter hub with instances a containerized jupyter notebook with multiple kernels on Arch Linux?
  • genotype-tissue expression GTEx
  • Active inference on discrete state-spaces - a synthesis by Lancelot Da Costa, Thomas Parr, Karl Friston et al in 2020
  • Bayesian brain hypothesis
  • web development
  • wikipedia
  • wine
  • videography
  • url
  • variational autoencoder
  • transfusion
  • transfusion medicine
  • turing.jl
  • tutorial
  • twitter
  • time
  • time series
  • transcriptomics
  • theoretical physics
  • television
  • terraform
  • systems biology
  • systems science
  • talk
  • structural stability
  • suppressed correlative
  • symmetry
  • symmetry analysis of dynamical systems
  • symmetry magazine
  • state
  • statistics
  • spinor bundle
  • softmax function
  • software library
  • source
  • spin group
  • single-cell variational inference
  • skim pdf reader
  • setup an inexpensive gke kubernetes cluster with no load balancer using terraform
  • setup calibre web server from docker container on kubernetes cluster
  • simulation
  • science
  • scVI
  • root android tablet with lineage os
  • scRNA-seq
  • renormalization
  • representation theory
  • restricted Boltzmann machine
  • references
  • reinforcement learning
  • quantum computation
  • quantum field theory
  • quantum mechanics
  • questions
  • random dynamical systems
  • public key infrastructure
  • pyclone
  • pyprob
  • pyro
  • python
  • programming languages
  • progress indicators
  • process philosophy
  • process philosophy a survey of basic issues by Nicholas Rescher in 2000
  • principal bundle
  • probabilistic programming
  • pragmatism
  • pragmatism in philosophical inquiry by Nicholas Rescher in 2016
  • pragmatism The Restoration of Its Scientific Roots by Nicholas Rescher in 2012
  • prediction error minimization
  • predictive coding model
  • predictive information maximization
  • political science
  • phase transition
  • phylogenetics
  • personal knowledge management
  • pedagogy
  • path integral
  • origin of life
  • oura ring
  • papers
  • parks
  • partial information decomposition
  • operate self-managed kubernetes cluster with kops
  • optimal transport
  • ocaml
  • nextjournal
  • noema
  • noesis
  • normalized exponential function
  • mutual information
  • natural units
  • network inference
  • monad-bayes
  • multi-level summaries
  • multiomics
  • mobility
  • model construction
  • moldable development
  • molecular biology
  • mendeley
  • metacademy
  • microbiology
  • mean-field approximation
  • mean-field approximation
  • measurement of biological systems
  • media
  • mathematical models of evolution
  • mathematical models of physiology
  • mathematics
  • maximal mutual information principle
  • literature
  • logic
  • logistic sigmoid function
  • manim
  • marginal observations
  • law
  • learning
  • lectures
  • library
  • kubernetes
  • large deviations
  • latent variable models
  • jupyter notebooks
  • kalman filters
  • key subsection
  • kops
  • julia
  • intrinsic motivation
  • invariant measures of random dynamical systems as analogs to attractors in deterministic dynamical systems
  • jazz
  • inference compilation
  • information
  • information bottleneck method
  • information geometry
  • hip hop
  • immunology
  • hidden markov models
  • hierarchical modularity
  • high energy physics
  • hiking routes
  • happiness
  • haskell
  • google photos
  • grand unified theories
  • hacker news
  • google cloud AI platform notebooks
  • google cloud platform
  • google cloud platform cloud architect training
  • google colab
  • genotype-phenotype map
  • geochemistry
  • giving presentations in roam
  • gene expression dynamics
  • gene panel
  • general relativity
  • genomics
  • fuzzy file finder
  • game theory
  • gauge gravitation theory
  • gauge theory
  • foam personal knowledge management for VS Code
  • frame bundle
  • find open source method of annotating pdfs in the web browser
  • farming
  • fcs file format
  • fiber bundle
  • evolutionary timescale
  • example
  • experimental evolution
  • factor analysis
  • evolution in fluctuating environments
  • evolution of multicelluarity
  • elasticsearch for pdf libraries
  • electromagnetism
  • embed
  • empowerment maximization
  • dynamics of biological systems
  • ecology
  • economics
  • effective theories
  • elasticsearch
  • docker compose
  • dynamic causal modeling
  • dynamical systems
  • differential geometry
  • digital computation
  • data analysis
  • definition
  • deleuze
  • dashboards from jupyter notebooks
  • continuous deployment to kubernetes
  • coq
  • course
  • computer algebra
  • computer science
  • contact
  • computational complexity
  • computational mechanics
  • coggle.it mind mapping
  • cognitive biases
  • cognitive science
  • collectors fallacy
  • cloud computing
  • cluster of differentiation markers
  • code repository
  • classical music
  • clipy
  • clothing
  • cancer evolution
  • category theory
  • causal inference
  • chemical reaction network theory
  • chemistry
  • brilliant.org
  • calculus of inductive constructions
  • calibre
  • biology
  • blog
  • books
  • branching processes
  • baryogenesis
  • basketball
  • biochemistry
  • bioinformatics
  • asexual evolution
  • associated bundle
  • associated projects
  • audio editing
  • applications of stochastic processes
  • approximate bayesian computation scheme for parameter inference and model selection in dynamical systems by Tina Toni, Michael P. H. Stumpf et al in 2009
  • analytic vs continental philosophy
  • animation
  • anthos
  • algorithms
  • a containerized emacs cloud multikernel notebook
  • active inference
  • Will Schoder
  • William Bialek
  • William James
  • Wolfram physics project
  • Whitehead's conceptual vocabulary for process philosophy
  • Whitehead's philosophy points of connection edited by Polanowski and Sherburne in 2004
  • Wilfrid Sellars
  • Whatever next? Predictive brains, situated agents, and the future of cognitive science by Andy Clark in 2013
  • What is a tensor? by XylyXylyX
  • What is general relativity? by XylyXylyX
  • What are good sources of news?
  • What does biology tell us about the kinds of information essential to the living state?
  • What is a manifold? by XylyXylyX
  • What is a statistical model by Peter McCullagh in 2002
  • What It Is Like to Perceive Direct Realism and the Phenomenal Character of Perception by J Christopher Maloney in 2018
  • What Is a Macrostate? Subjective Observations and Objective Dynamics by Cosma Shalizi and Chris Moore in 2003
  • Virasoro algebra
  • Visualizing probabilistic models in Minkowski space with intensive symmetrized Kullback-Leibler embedding by Han Teoh, Katherine Quinn, James Sethna et al in 2020
  • Voyage of time
  • W. Ross Ashby
  • Variational inference a review for statisticians by David Blei et al in 2017
  • Variational inference by Chieh Wu in 2015
  • Video
  • VPRO documentary
  • Undark
  • Universal Darwinism as a process of Bayesian inference by John Campbell in 2016
  • Tug-of-war between driver and passenger mutations in cancer and other adaptive processes by McFarland Mirny and Korolev in 2014
  • Tumour heterogeneity and the evolutionary trade-offs of cancer by Hausser and Alon in 2020
  • UMAP
  • True to form by Eric Goodman in 2016
  • Tudor Girba
  • Thermodynamics of Open Chemical Reaction Networks Theory and Applications by Massimiliano Esposito in 2020
  • Thinking with Whitehead by Isabelle Stengers
  • Three Billboards outside Ebbing, Missouri
  • The unitary representations of the Poincare group in any spacetime dimension by Xavier Bekaert and Nicolas Boulanger in 2006
  • The usual suspects
  • The way of the gun
  • Theoretical investigations of an information geometric approach to complexity by Sean Ali and Carlo Cafaro in 2017
  • The pragmatic turn by Richard Bernstein in 2010
  • The predictive mind by Jakob Hohwy in 2013
  • The speed of evolution in large asexual populations by Krug et al in 2010
  • The importance of mechanisms for the evolution of cooperation by Pieter van den Berg and Franz Weissing
  • The geometry of physics by Theodore Frankel in 2012
  • The glass bead game by Hermann Hesse in 1943
  • The hudsucker proxy
  • The evolutionary dynamics and fitness landscape of clonal hematopoiesis by Caroline Watson, Daniel Fisher, Jamie Blundell, et al in 2020
  • The frequency-dependent Wright–Fisher model diffusive and non-diffusive approximations by Fabio Chalub and Max Souza in 2014
  • The cellular automaton interpretation of quantum mechanics by Gerard 't Hooft in 2014
  • The checklist manifesto
  • The demon in the machine by Paul Davies in 2019
  • The end of objectivity by Gian-Carlo Rota in 1973
  • The evolution of cellular individuality by Eric Deeds in 2019
  • The ballad of Buster Scruggs
  • The big lebowski
  • The causes of molecular evolution by John Gillespie in 1994
  • The World A brief introduction by Richard Haass in 2020
  • The Structure and Interpretation of the Standard Model by Gordon McCabe in 2007
  • The Tree of Life
  • The Value of Information for Populations in Varying Environments by Rivoire and Leibler in 2011
  • The Rise of Modern Philosophy A New History of Western Philosophy, Vol. III
  • The Road to Reality by Roger Penrose in 2004
  • The Scientific Method An Evolution of Thinking from Darwin to Dewey by Henry Cowles in 2020
  • The Self-Evidencing Brain by Jakob Hohwy in 2016
  • The Knowledge Economy by Roberto Mangabeira Unger in 2019
  • The Man from UNCLE
  • The Financial Times
  • The Gentlemen
  • The Graph, Wall, Tome project of Eric Weinstein's Portal Community
  • The Helmholtz Machine by Peter Dayan, Geoffrey Hinton, Radford Neal, and Richard Zemel in 1995
  • The Atlantic
  • The Correspondent
  • Tensor manipulation in GPL Maxima by Viktor Toth in 2007
  • The 2010s Our Decade of Deep Learning Outlook on the 2020s by Jürgen Schmidhuber in 2020
  • Succession
  • Symmetry analysis of differential equations by Gerd Baumann in 2000
  • Synthetic philosophy of contemporary mathematics by Fernando Zalamea in 2012
  • Systematically Improving Espresso Insights from Mathematical Modeling and Experiment by Michael Cameron, Christopher Hendon, and Jamie Foster in 2020
  • String Theory and the Scientific Method by Richard Dawid in 2013
  • Structural stability and morphogenesis by Rene Thom in 1972
  • Subclonal reconstruction of tumors by using machine learning and population genetics by Giulio Caravagna, Marc Williams, Trevor Graham, and Andrea Sottoriva in 2020
  • Statistical rethinking by Richard McElreath in 2020
  • Stephen Wolfram
  • Stheno.jl
  • Statistical exponential families A digest with flash cards by Frank Nielsen and Vincent Garcia in 2011
  • Statistical inference for stochastic simulation models theory and application by Florian Hartig, Andreas Huth, et al in 2011
  • Statistical physics approaches to subnetwork dynamics in biochemical systems by Bravi and Sollich in 2017
  • Statistical physics of biological evolution by Krug in 2014
  • Stan
  • Stanford encyclopedia article on Gilles Deleuze
  • Stanford encyclopedia article on process philosophy
  • Statistical Physics of Complex Systems by Eric Bertin in 2016
  • Speed Limits by Mark C Taylor in 2014
  • Splatter simulation of single-cell RNA sequencing data by Luke Zappia, Belinda Phipson, and Alicia Oshlack
  • Solomonoff induction
  • Some Quantum Mechanical Properties of the Wolfram Model by Jonathan Gorard in 2020
  • Some Relativistic and Gravitational Properties of the Wolfram Model by Jonathan Gorard in 2020
  • Speculative Empiricism Revisiting Whitehead by Didier Debaise in 2017
  • SiCloneFit Bayesian inference of population structure, genotype, and phylogeny of tumor clones from single-cell genome sequencing data by Zafar and Nakhleh in 2019
  • Simulation of High-Energy Reactions of PArticles
  • Self-organization in nonequilibrium systems from dissipative structures to order through fluctuations by Nicolis and Prigogine in 1977
  • Sellars and his legacy by James O'Shea in 2017
  • SageManifolds
  • SageMath
  • Santa Fe Institute
  • Sara Imari Walker
  • Scale Up! by Odoo
  • Russ Salakhutdinov's lectures on Large Scale Machine Learning
  • Sabine Hossenfelder
  • SCANPY
  • Rivka Weinberg
  • Robert Brandom
  • Roberto Mangabeira Unger
  • Resolving genetic heterogeneity in cancer by Turajlic, Graham, and Swanton et al 2019
  • Revolver
  • Richard Rorty
  • Relating Fisher Information to order parameters by Mikhail Prokopenko, Rosalind Wang, et al in 2011
  • Relations and dependencies between morphological characters Jürgen Jost in 2017
  • Renormalization for Philosophers by Butterfield and Bouatta in 2014
  • Renormalization methods a guide for beginners by McComb in 2004
  • Realizing reason a narrative of truth and knowing by Danielle MacBeth in 2014
  • Regression and Other Stories by Andrew Gelman, Jennifer Hill, and Aki Vehtari in 2020
  • ReMixT Clone-specific genomic structure estimation in cancer by McPherson and Shah 2017
  • Quantum field theory for economics and finance by Belal Baaquie in 2018
  • Quantum mechanics and quantum field theory by Jonathan Dimock in 2011
  • Quanta magazine
  • Quantification of subclonal selection in cancer from bulk sequencing data by Williams and Graham in 2018
  • Quantum Bayesianism
  • Quantum Field Theory for the Gifted Amateur by Lancaster and Blundell in 2014
  • Quantum Processes A Whiteheadian Interpretation of Quantum Field Theory by Frank Hattich
  • Process and reality by Alfred North Whitehead in 1929
  • Programming Language Foundations in Agda by Philip Wadler in 2018
  • Project syndicate
  • Propublica
  • PyClone Statistical inference of clonal population structure in cancer by Roth and Shah in 2014
  • Probabilistic data clustering with a chemical mixture of biopolymers by Yarden Katz and Walter Fontana in 2019
  • Process Metaphysics An introduction to process philosophy by Nicholas Rescher in 1996
  • Process-relational philosophy by C. Robert Mesle in 2008
  • Population biology and criticality by Nico Stollenwerk and Vincent Johnson in 2010
  • Pragmatism, Objectivity, and Experience by Steven Levine in 2019
  • Predicting Evolutionary Constraints by Identifying Conflicting Demands in Regulatory Networks by Manjunatha Kogenaru, Frank Poelwijk, Sander Tans et al in 2020
  • Planning as Inference in Epidemiological Dynamics Models by Andrew Warrington, Saeid Naderiparizi, and Frank Wood in 2020
  • Population Genetics and Evolution by Joachim Krug in 2018
  • Philosophical perspectives by Max Scheler in 1929
  • Phylogenetic inference using RevBayes by Hohna, Landis, and Heath in 2017
  • Pattern recognition and machine learning by Chris Bishop in 2006
  • PBS frontline
  • PBS NewsHour
  • POMO
  • Optimal transport for Applied Mathematicians Calculus of Variations, PDEs, and Modeling by Filippo Santambrogio in 2015
  • Order out of chaos by Prigogine and Stengers in 1984
  • Out of Nature: How a Concept Became a Political Power? by Didier Debaise in 2019
  • Olivier Gandrillon
  • On the Classification of Dynamical Systems by Chris Zeeman in 1988
  • Optimal Renormalization Group Transformation from Information Theory by Lenggenhager, Ringel, Huber, and Koch-Janusz in 2018
  • Optimal transport Analysis of Single-Cell Gene Expression Identifies Developmental Trajectories in Reprogramming by Geoffrey Schiebinger, Aviv Regev, Eric Lander, et al in 2019
  • O Brother, Where art thou?
  • Normal Form for Renormalization Groups by Archishman Raju, James Sethna, et al in 2019
  • Notes on representation theory and quantum mechanics by Noah Miller in 2018
  • Notions of intrinsic motivation by Martin Biehl in 2017
  • OBS studio
  • Nonnegative Decomposition of Multivariate Information by Paul Williams and Randall Beer in 2010
  • Nature as Event The Lure of the Possible by Didier Debaise in 2017
  • Network inference and biological dynamics by Chris Oates and Sach Mukherjee in 2012
  • Network motifs in the transcriptional regulation network of Escherichia coli by Shen-Orr and Alon in 2002
  • Multiscale Structure in Eco-Evolutionary Dynamics by Blake Stacey in 2015
  • Naftali Tishby
  • Naturalizing Badiou by Fabio Gironi in 2014
  • Model reduction methods for classical stochastic systems with fast-switching environments reduced master equations, stochastic differential equations, and applications by Hufton, Lin, and Galla in 2018
  • Multi-cancer analysis of clonality and the timing of systemic spread in paired primary tumors and metastases by Zheng Hu, Christina Curtis, et al in 2020
  • Multi-Omics Factor Analysis v2 MOFA+ a statistical framework for comprehensive integration of multi-modal single-cell data by Ricard Argelaguet, Oliver Stegle, et al in 2020
  • Mikhail Tikhonov
  • Mehran Kardar
  • Michael I. Jordan
  • Michael P. H. Stumpf
  • Mean field variational inference
  • Measuring Clonal Evolution in Cancer with Genomics by Williams, Sottoriva, and Graham in 2019
  • Mechanistic Inference of Brain Network Dynamics with Approximate Bayesian Computation by Timothy West, Vladimir Litvak, et al in 2019
  • Master equations and the theory of stochastic path integrals by Markus Weber and Erwin Frey in 2017
  • Mathematical concepts by Jurgen Jost in 2015
  • Mathematical modeling with single-cell sequencing data by Heyrim Cho and Russell Rockne in 2019
  • Mathieu Boespflug
  • Markov blankets, information geometry and stochastic thermodynamics by Parr and Friston in 2020
  • Markov processes
  • Markov Processes for Stochastic Modeling by Oliver Ibe in 2013
  • Marcus Hutter
  • Making it explicit by Robert Brandom in 1998
  • Lock, stock, and two smoking barrels
  • Logic of Worlds Being and Event by Alain Badiou in 2009
  • Looper
  • Large deviations and dynamical phase transitions in stochastic chemical networks by Lazarescu and Esposito in 2019
  • Lectures on Geometrical Anatomy of Theoretical Physics by Frederic Schuller in 2015
  • Lie algebras
  • Lie groups
  • Konrad Zuse
  • LaTeX fonts
  • Jurgen Habermas
  • Jurgen Jost
  • Karl Friston
  • Kelly Starrett
  • Juergen Schmidhuber
  • Jonathan Gorard
  • Joscha Bach
  • John Hopfield
  • John McDowell
  • Jennifer Hill
  • Joachim Krug
  • Joachim Krug ICTS Lectures June 2019
  • Jan Hasenauer
  • Introductory Lectures on Stochastic Population Systems by Donald Dawson in 2017
  • Isabelle Stengers
  • Jakob Hohwy
  • James Sethna
  • Introduction to dynamical large deviations of Markov processes by Hugo Touchette in 2018
  • Introduction to single-cell Variational Inference
  • Introduction to symmetry analysis by Brian Cantwell in 2002
  • Introduction to the Standard Model of Particle Physics by Rainer Hauser and Alex Flournoy in 2019
  • Information geometry by Nihat Ay, Jurgen Jost, et al in 2017
  • Information Theory for Fields by Torsten Enslin in 2019
  • Intelligence and spirit by Reza Negarestani in 2018
  • Interfaces of Malignant and Immunologic Clonal Dynamics in Ovarian Cancer by Zhang and Shah in 2018
  • Intrinsic and extrinsic thermodynamics for stochastic population processes with multi-level large-deviation structure by Eric Smith in 2020
  • Inferring gene regulatory networks from single-cell data a mechanistic approach by Ulysse Herbach, Olivier Gandrillon, et al in 2017
  • Inferring what to do (and what not to) by Thomas Parr in 2020
  • Information Geometry and Population Genetics by Julian Hofrichter, Jurgen Jost, and Tat Dat Tran in 2017
  • Information, physics, and computation by Marc Mezard and Andrea Montanari in 2009
  • Immanuel Kant
  • In what sense can gene-regulatory networks be thought of as performing inference upon the dynamics of the environments within which they are embedded?
  • Inferring Interaction Networks From Multi-Omics Data by Johann Hawe, Fabian Theis, and Matthias Heinig in 2019
  • Husserlian phenomenology
  • If a cell was performing probabilistic inference how could this be measured experimentally?
  • Immanuel Kant's three philosophical questions
  • How to construct and debug a dockerfile
  • How to take smart notes by Sonke Ahrens in 2017
  • How to win in a winner-takes-all world by Neil Irwin in 2019
  • Hunt for the Wilderpeople
  • How can we develop transformative tools for thought? by Andy Matuschak and Michael Nielsen in 2019
  • How is digital physics related to the free energy principle?
  • Higher prequantum geometry by Urs Schreiber in 2017
  • History of Western Philosophy by Anthony Kenny
  • Herbert Simon
  • Herbert Simon's parable of two watchmakers
  • Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters by James Hensman, Neil Lawrence, and Magnus Rattray in 2013
  • Hans Reichenbach's vindication of induction by Wesley Salmon in 1991
  • Hematopathology, 2nd edition by Jaffe, Arber, Campo, Harris, and Quintanilla-Martinez
  • Group theory in a nutshell for physicists by Anthony Zee in 2016
  • Gilles Deleuze An Introduction by Todd May in 2015
  • Godel's incompleteness theorem
  • GpABC a Julia package for approximate bayesian computation with Gaussian process emulation by Evgeny Tankhilevich, Michael P. H. Stumpf et al in 2020
  • Gravitation by Misner, Thorne, and Wheeler in 1970
  • Georg Hegel
  • George Box
  • Gilles Deleuze
  • Geometry and Physics by Jurgen Jost in 2009
  • Geometry of Friston's active inference by Martin Biehl in 2018
  • Geometry of physics by Urs Schreiber
  • Geometry, Topology, and Physics by Mikio Nakahara in 2003
  • Gaussian processes for time-series modelling by Roberts, Osborne, Aigrain, et al in 2013
  • Gene Regulatory Network Inference from Single-Cell Data Using Multivariate Information Measures by Thalia Chan, Michael P. H. Stumpf, and Ann C. Babtie in 2017
  • Gene regulatory network inference from sparsely sampled noisy data by Atte Aalto, Jorge Goncalves, et al in 2020
  • Geometric unity by Eric Weinstein in 2013
  • Gauge Theories in Particle Physics A Practical Introduction by Aitchison and Hey in 2013
  • Gauge Theories in Particle Physics A Practical Introduction, Volume 2 Non-Abelian Gauge Theories QCD and The Electroweak Theory by Aitchison and Hey in 2013
  • Gaussian process
  • Gauge Theories in Particle Physics A Practical Introduction, Volume 1 From Relativistic Quantum Mechanics to QED by Aitchison and Hey in 2013
  • From computation to consciousness by Joscha Bach in 2014
  • From computation to life The challenge of a science of organization by Walter Fontana in 2020
  • Functional Differential Geometry by Sussman, Wisom, and Farr in 2013
  • Foreign affairs magazine
  • Formally justified and modular Bayesian inference for probabilistic programs by Adam Michal Scibior in 2018
  • Francis Miller
  • Frank Wood
  • Free Energy, Value, and Attractors by Friston and Ao in 2012
  • Finite and infinite games A vision of life as play and possibility by James Carse in 1986
  • Flaviano Morone
  • Fibration symmetries uncover the building blocks of biological networks by Flaviano Morone and Hernan Makse in 2020
  • Fareed Zakaria's GPS
  • Fargo
  • Fate of a mutation in a fluctuating environment by Cvijovic, Good, and Desai in 2015
  • Expanding the Active Inference Landscape More Intrinsic Motivations in the Perception-Action Loop by Martin Biehl, Daniel Polani, et al in 2018
  • Fabian Theis
  • Fabio Gironi
  • Evolutionary game theory theoretical concepts and applications to microbial communities by Erwin Frey in 2010
  • Evolutionary Phase Transitions in Random Environments by Skanata and Kussell in 2016
  • EvolutionaryDynamics.jl
  • Ex machina
  • Exact solution of a two-type branching process clone size distribution in cell division kinetics by Antal and Krapivsky in 2010
  • Evaluating probabilistic programming and fast variational Bayesian inference in phylogenetics by Mathieu Fourment and Aaron Darling in 2019
  • Evergreen notes by Andy Matuschak
  • Evolution and Selection of Quantitative Traits by Bruce Walsh and Michael Lynch in 2018
  • Evolution of multiple cell clones over a 29-year period of a CLL patient by Zhikun Zhao, Michael Dean, et al in 2016
  • Eric Weinstein
  • Erwin Frey
  • Embodying probabilistic inference in biochemical circuits by Yarden Katz, Michael Springer, and Walter Fontana in 2018
  • Epistemology An introduction to the theory of knowledge by Nicholas Rescher in 2003
  • Effective fluctuation and response theory by Polettini and Esposito in 2018
  • Efficient exact inference for dynamical systems with noisy measurements using sequential approximate bayesian computation by Yannik Schalte and Jan Hasenauer in 2020
  • Efficient probabilistic inference in the quest for physics beyond the Standard Model by Atilim Baydin, Frank Wood et al in 2019
  • Economic alternatives for the future by Roberto Mangabeira Unger in 2020
  • Edmund Husserl
  • Effective Field Theories, Reductionism and Scientific Explanation by Stephan Hartmann in 2001
  • ETH probabilistic AI course
  • Du Phan
  • Du Phan's implementation of Statistical rethinking in pyro
  • Dynamical Systems Examples of Complex Behavior by Jurgen Jost in 2005
  • Defining Network Topologies that Can Achieve Biochemical Adaptation by Wenzhe Ma, Hana El-Samad, Wendell Lim, and Chao Tang in 2009
  • Dirichlet process mixture model
  • Doi-Peliti Path Integral Methods
  • Danielle MacBeth
  • David Blei
  • David Deutsch
  • David Duvenaud
  • Daniel Murfet
  • Daniel Polani
  • Daniel Sacilotto
  • DPMM-GP model
  • DW documentary
  • Current best practices in single‐cell RNA‐seq analysis a tutorial by Malta Luecken and Fabian Theis in 2019
  • Curry-Howard isomorphism
  • DEM A variational treatment of dynamic systems by Karl Friston and J Daunizeau in 2008
  • Consciousness and intentionality in the Stanford Encyclopedia of Philosophy
  • Cosma Shalizi
  • Council on foreign relations
  • Courses
  • Covariant Loop Quantum Gravity An Elementary Introduction to Quantum Gravity and Spinfoam Theory by Rovelli and Vidotto in 2014
  • Clifford algebras
  • Clustering gene expression time series data using an infinite Gaussian process mixture model by Ian McDowell, Timothy Reddy, Barbara Engelhardt, et al in 2018
  • Computational resource demands of a predictive Bayesian brain by Johan Kwisthout and Iris van Rooij in 2020
  • Charles Sanders Peirce
  • Chris Bishop
  • Circuits with broken fibration symmetries perform core logic computations in biological networks by Ian Leifer, Flaviano Morone, and Hernan Makse in 2020
  • Cash truck
  • Catalogue of Spacetimes by Mueller and Grave in 2009
  • Causal inference with Bayes rule by Finnian Lattimore and David Rohde in 2019
  • Causal network inference using biochemical kinetics by Chris Oates, Sach Mukherjee et al in 2014
  • Build, Compute, Critique, Repeat Data Analysis with latent variable models by David Blei in 2014
  • Brian Cantwell
  • Bloomberg
  • Branching process models of cancer by Durrett in 2015
  • Branching processes by Athreya and Ney in 1972
  • Blake Stacey
  • Better things
  • Between-region genetic divergence reflects the mode and tempo of tumor evolution by Ruping Sun, Zheng Hu, Andrea Sottoriva, Trevor Graham, and Christina Curtis in 2017
  • Becoming a supple leopard by Kelly Starrett in 2015
  • Becoming as inference
  • Bayesian non-parametrics and the probabilistic approach to modelling by Zoubin Ghahramani in 2013
  • Bayesian reasoning and machine learning by David Barber in 2012
  • Bayesian biology hypothesis
  • Bayesian chemistry hypothesis
  • Barton Fink
  • Baruch Spinoza
  • Bayesian Inference for a Generative Model of Transcriptome Profiles from Single-cell RNA Sequencing by Romain Lopez, Michael Jordan, Nir Yosef et al in 2018
  • Automatic Differentiation Variational Inference by Dustin Tran, Andrew Gelman, David Blei et al in 2016
  • Arthur Franz
  • Articulating reasons An introduction to inferentialism by Robert Brandom in 2000
  • Asexual evolution waves fluctuations and universality by Daniel Fisher in 2013
  • Audio
  • Approximation and inference methods for stochastic biochemical kinetics—a tutorial review by David Schnoerr, Guido Sanguinetti and Ramon Grima in 2017
  • Approximate Bayesian inference in semi-mechanistic models by Andrej Aderhold, Dirk Husmeier, and Marco Grzegorczyk in 2017
  • An introduction to the mathematical structure of the Wright-Fisher model of population genetics by Julian Hofrichter, Jurgen Jost, and Tat Dat Tran in 2013
  • Andrew Gelman
  • Andy Clark
  • An introduction to manifolds by Loring Tu in 2010
  • An introduction to probabilistic programming by Jan-Willem van de Meent, Frank Wood et al in 2018
  • Alfred North Whitehead
  • An Introduction to Systems Biology by Uri Alon in 2020
  • Adam Michal Scibior
  • Alain Badiou
  • A theory of incremental compression by Arthur Franz et al in 2019
  • A tutorial on the free-energy framework for modeling perception and learning by Rafal Bogacz in 2017
  • A mathematical introduction to conformal field theory by Martin Schottenloher in 2008
  • A new kind of science by Stephen Wolfram in 2002
  • A theory of cortical responses by Karl Friston in 2005
  • A free energy principle for a particular physics by Karl Friston in 2019
  • A high-bias, low-variance introduction to Machine Learning for physicists by Pankaj Mehta, Charles Fisher, David Schwab, et al in 2018
  • A brief history of Western Philosophy by Anthony Kenny in 2019
  • A critical history of renormalization by Kerson Huang in 2013
  • A framework for parameter estimation and model selection from experimental data in systems biology using approximate bayesian computation by Juliane Liepe, Michael P. H. Stumpf et al in 2014
  • A General Relativity Workbook by Thomas Moore in 2010
  • A Hidden Life
  • A Simulated Annealing Approach to Bayesian Inference by Carlo Albert in 2018
  • A Spirit of Trust by Robert Brandom in 2019
  • 60 minutes
  • A Class of Models with the Potential to Represent Fundamental Physics by Stephen Wolfram in 2020