Pinboard (mraginsky)
https://pinboard.in/u:mraginsky/public/
recent bookmarks from mraginsky[2602.04770] Generative Modeling via Drifting2026-06-24T17:26:20+00:00
https://arxiv.org/abs/2602.04770
mraginskypapers to-read generative-models diffusions neural-networkshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:23902c99e580/[2507.10524] Mixture-of-Recursions: Learning Dynamic Recursive Depths for Adaptive Token-Level Computation2026-06-24T17:25:58+00:00
https://arxiv.org/abs/2507.10524
mraginskypapers to-read machine-learning neural-networks large-language-models transformershttps://pinboard.in/https://pinboard.in/u:mraginsky/b:766a4f286462/For a probabilistic sociology: A history of concept formation with Pierre Bourdieu | Theory and Society | Springer Nature Link2026-06-21T00:40:23+00:00
https://link.springer.com/article/10.1007/s11186-021-09452-2
mraginskypapers to-read sociology via:rvenkathttps://pinboard.in/https://pinboard.in/u:mraginsky/b:c10a7d697e14/jmlr.org/papers/v3/bengio03a.html2026-06-17T20:39:23+00:00
https://www.jmlr.org/papers/v3/bengio03a.html
mraginskypapers to-read language machine-learning neural-networks large-language-modelshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:4c52bf105324/[2606.13280] Generalization Bounds for Transformer-Based Next-Token Prediction in a Language Model2026-06-16T13:55:17+00:00
https://arxiv.org/abs/2606.13280
mraginskypapers to-read machine-learning generalization-bounds transformers large-language-modelshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:a5c4d1b8ae13/Reassessing the “rules of the game”: Max Weber and Peter Winch on rule-following - Akos Sivado, 20202026-06-09T15:50:47+00:00
https://journals.sagepub.com/doi/10.1177/1468795X18817146
mraginskypapers to-read philosophy sociology ruleshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:2157d12afade/Random Tree Model of Meaningful Memory | Phys. Rev. Lett.2026-06-08T17:18:34+00:00
https://journals.aps.org/prl/abstract/10.1103/g1cz-wk1l
mraginskypapers to-read memory random-structures language statistical-physicshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:5718d5c7a886/Information rate of meaningful communication | PNAS2026-06-08T17:17:22+00:00
https://www.pnas.org/doi/full/10.1073/pnas.2502353122
mraginskypapers to-read information-theory language large-language-models communication semantic-communicationhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:c67a307c255b/[2603.11784] Language Generation with Replay: A Learning-Theoretic View of Model Collapse2026-06-08T13:12:15+00:00
https://arxiv.org/abs/2603.11784
mraginskypapers to-read large-language-models model-collapse learning-theoryhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:00b4a96208c9/What are emergent properties and how do they affect the engineering of complex systems? - ScienceDirect2026-06-07T21:39:25+00:00
https://www.sciencedirect.com/science/article/pii/S0951832006000330
mraginskypapers to-read complex-systems engineeringhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:777c41184f9a/Resolving Feynman’s restaurant problem reveals optimal solutions and human strategies | PNAS2026-06-07T20:54:23+00:00
https://www.pnas.org/doi/10.1073/pnas.2509612123
mraginskypapers to-read optimal-stopping decision-making Feynmanhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:ed1a3861ba75/It’s not the thought that counts: Allostasis at the core of brain function: Neuron2026-06-02T23:33:52+00:00
https://www.cell.com/neuron/fulltext/S0896-6273(25)00716-0?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0896627325007160%3Fshowall%3Dtrue
mraginskypapers to-read neuroscience control-theory dynamical-systems cognitionhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:0eecd28934b3/Small Probabilities and High Stakes2026-05-19T16:16:30+00:00
https://www.cambridge.org/core/elements/small-probabilities-and-high-stakes/13D562255077904A204C8659BD0AB34F?utm_id=97758_v0_s00_e231_tv4_tp1_a1dennhawg2fhs&fbclid=IwY2xjawR5aspleHRuA2FlbQIxMABicmlkETFCNDcyd0ZBT0g0aWMwN01ic3J0YwZhcHBfaWQQMjIyMDM5MTc4ODIwMDg5MgABHsqqQ3oKimlTk8OOI5JVSdwaeJ14tae_kosyVOjfV8lMxZevM9qLTga0e12V_aem_7OG_-ZBz2GaUiibkJ0j-bA
mraginskyto-read books-noted philosophy decision-theory probabilismhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:fe7b313a9824/The overlap gap property: A topological barrier to optimizing over random structures | PNAS2026-05-13T17:37:50+00:00
https://www.pnas.org/doi/10.1073/pnas.2108492118
mraginskypapers to-read computational-complexity random-structures statistical-physicshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:483a65f6c008/[2510.15464] Learning to Answer from Correct Demonstrations2026-05-11T19:34:28+00:00
https://arxiv.org/abs/2510.15464
mraginskypapers to-read heard-the-talk large-language-models machine-learninghttps://pinboard.in/https://pinboard.in/u:mraginsky/b:f5836b2d0d6b/The problem of induction (heads), pt. I - by Sean Trott2026-05-10T00:52:13+00:00
https://seantrott.substack.com/p/the-problem-of-induction-heads-pt
mraginskyblogs to-read large-language-models machine-learning neural-networkshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:7330918ac7dd/Neural correlates of perceptual decision-making in the primary somatosensory cortex | PNAS2026-05-10T00:51:01+00:00
https://www.pnas.org/doi/10.1073/pnas.2514107123
mraginskypapers to-read neuroscience decision-making perceptionhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:5060bdd7f851/[2410.01576] On incompressible flows in discrete networks and Shnirelman's inequality2026-05-10T00:50:27+00:00
https://arxiv.org/abs/2410.01576
mraginskypapers to-read dynamical-systems PDEshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:0d9ac4075df5/[2605.01172] A Theory of Generalization in Deep Learning2026-05-10T00:44:31+00:00
https://arxiv.org/abs/2605.01172
mraginskypapers to-read learning-theory machine-learning deep-learning dynamical-systems optimization neural-networks generalization-boundshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:5ed6efa9c148/The future of control - ScienceDirect2026-05-05T18:12:23+00:00
https://www.sciencedirect.com/science/article/pii/000510987790022X
mraginskyto-read control-theory engineering complex-systems computationhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:5c08fa3aa2c7/On computing quantum waves exactly from classical action | Proceedings A | The Royal Society2026-05-01T15:55:32+00:00
https://royalsocietypublishing.org/rspa/article/482/2336/20250413/481461/On-computing-quantum-waves-exactly-from-classical
mraginskypapers to-read physics dynamical-systems quantum-mechanics color-me-skepticalhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:10c52d2df623/[2602.07488] Deriving Neural Scaling Laws from the statistics of natural language2026-05-01T15:53:17+00:00
https://arxiv.org/abs/2602.07488
mraginskypapers to-read large-language-models neural-networks deep-learning machine-learninghttps://pinboard.in/https://pinboard.in/u:mraginsky/b:c9205d53524e/[2604.21691] There Will Be a Scientific Theory of Deep Learning2026-05-01T15:46:32+00:00
https://arxiv.org/abs/2604.21691
mraginskypapers to-read machine-learning deep-learning neural-networkshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:42dc3c1e01b6/Instrumental Variables: An Econometrician’s Perspective2026-04-29T14:47:59+00:00
https://projecteuclid.org/journals/statistical-science/volume-29/issue-3/Instrumental-Variables-An-Econometricians-Perspective/10.1214/14-STS480.full
mraginskypapers to-read statistics inference instrumental-variables econometrics randomized-experiments experimental-designhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:ea6321f5a7bc/Probabilistic Kernel Regression Models2026-04-25T02:13:48+00:00
https://proceedings.mlr.press/r2/jaakkola99a.html
mraginskypapers to-read kernel-methods machine-learning optimizationhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:2ecbc0a0a1a8/Unveiling the Hidden Structure of Self-Attention via Kernel Principal Component Analysis2026-04-25T02:13:05+00:00
https://proceedings.neurips.cc/paper_files/paper/2024/hash/b78adc1c1558bf344809275854d40fd6-Abstract-Conference.html
mraginskypapers to-read transformers large-language-models kernel-methodshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:150df429d4fb/Language Generation in the Limit | OpenReview2026-04-24T20:43:14+00:00
https://openreview.net/forum?id=FGTDe6EA0B&referrer=%5Bthe%20profile%20of%20Jon%20Kleinberg%5D(%2Fprofile%3Fid%3D~Jon_Kleinberg3)
mraginskypapers to-read heard-the-talk language generative-models computer-sciencehttps://pinboard.in/https://pinboard.in/u:mraginsky/b:cf4b581b7488/Standards for Modest Bayesian Credences | Philosophy of Science | Cambridge Core2026-04-24T15:58:54+00:00
https://www.cambridge.org/core/journals/philosophy-of-science/article/standards-for-modest-bayesian-credences/6FE3D870363912FE2EE5596E734D4B0B
mraginskypapers to-read philosophy-of-probability epistemology bayesianism probabilismhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:a7a9d7acc836/[2306.00802] Birth of a Transformer: A Memory Viewpoint2026-04-24T15:07:11+00:00
https://arxiv.org/abs/2306.00802
mraginskypapers to-read transformers large-language-modelshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:d133c450f867/Attaining the Chebyshev bound for optimal learning: A numerical algorithm - ScienceDirect2026-04-23T02:52:00+00:00
https://www.sciencedirect.com/science/article/pii/S0167691123001950?via%3Dihub
mraginskypapers to-read optimal-recovery interpolation numerical-methods optimizationhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:f58628d99e17/Abstraction as flexibility: the veil of evaluative uncertainty | Economics & Philosophy | Cambridge Core2026-04-22T00:51:02+00:00
https://www.cambridge.org/core/journals/economics-and-philosophy/article/abstraction-as-flexibility-the-veil-of-evaluative-uncertainty/FA12D9D5BB3783F8EACF396DFE4B93EB
mraginskypapers to-read abstractions rationality decision-theory game-theory economicshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:31b1026460d0/Linear PDE with constant coefficients | Glasgow Mathematical Journal | Cambridge Core2026-04-22T00:50:12+00:00
https://www.cambridge.org/core/journals/glasgow-mathematical-journal/article/linear-pde-with-constant-coefficients/E406F1D5A27DC4B4414B8A3DF3A225F6
mraginskypapers to-read PDEs differential-algebra polynomials commutative-algebrahttps://pinboard.in/https://pinboard.in/u:mraginsky/b:3447f4cbf0c1/Dependency syntax as the simplest theory of grammar: Trends in Cognitive Sciences2026-04-20T18:04:17+00:00
https://www.cell.com/trends/cognitive-sciences/fulltext/S1364-6613(26)00052-5
mraginskypapers to-read language learning grammar syntaxhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:710cc64ef785/Engels' Pause and the Permanent Underclass2026-04-19T01:49:23+00:00
https://www.fabricatedknowledge.com/p/mythos-and-engels-pause?fbclid=IwY2xjawRPrTNleHRuA2FlbQIxMQBicmlkETE4eDlndjllUld2cjlBTkFzc3J0YwZhcHBfaWQQMjIyMDM5MTc4ODIwMDg5MgABHsMwf89zs3VKJoXCiZg-1RshLfpVCcwbEgNOrrL2erKG5FX6sPEz6qE5axUQ_aem_RVUflDX1Xm89FsiXcKYlDQ
mraginskyblogs to-read ai security computation economics technologyhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:4b2e91f0df03/Defeating Nondeterminism in LLM Inference - Thinking Machines Lab2026-04-18T22:13:14+00:00
https://thinkingmachines.ai/blog/defeating-nondeterminism-in-llm-inference/
mraginskyto-read ai machine-learning determinism large-language-models computationhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:24aaffeb64a7/AI Can’t Replace Free Markets - WSJ2026-04-18T22:11:27+00:00
https://archive.is/DKKXJ
mraginskyto-read ai economics decentralized-control complexityhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:80d5ce52266b/"Artificial Bodies and the Promise of Abstraction": a conversation with Peter Wolfendale (Keywords: Philosophy of Mind; Phenomenology; Embodiment)2026-04-18T21:20:47+00:00
https://www.thephilosopher1923.org/post/artificial-bodies-and-the-promise-of-abstraction
mraginskyto-read philosophy cognitive-science embodiment aihttps://pinboard.in/https://pinboard.in/u:mraginsky/b:aa3cab335182/AI Doesn’t Reduce Work—It Intensifies It2026-04-18T21:20:15+00:00
https://hbr.org/2026/02/ai-doesnt-reduce-work-it-intensifies-it
mraginskyto-read ai economics labor capital productivityhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:f56f3e30c0cd/The Market as a Creative Process | Economics & Philosophy | Cambridge Core2026-04-18T21:19:33+00:00
https://www.cambridge.org/core/journals/economics-and-philosophy/article/market-as-a-creative-process/4A62A60230535D4A8553A7C26A184F56
mraginskypapers to-read economics dynamical-systems complex-systems process-philosophy evolutionhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:7f64a7342065/Making Machine Learning Safe for the World - New Lines Institute2026-04-15T19:44:51+00:00
https://newlinesinstitute.org/tech-econ-sov-sec/making-machine-learning-safe-for-the-world/
mraginskyto-read machine-learning ai economics policy technology securityhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:7a98e5d9333b/[2604.06107] Artificial Intelligence and the Structure of Mathematics2026-04-12T16:10:36+00:00
https://arxiv.org/abs/2604.06107
mraginskypapers to-read mathematics ai philosophyhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:2445d9d7f6fd/Agnostic Insurability of Model Classes2026-04-01T15:00:12+00:00
https://jmlr.org/papers/v16/santhanam15a.html
mraginskypapers to-read machine-learning universal-predictionhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:02e7d901124d/Feelings Are the Source of Consciousness | Neural Computation | MIT Press2026-03-06T15:38:38+00:00
https://direct.mit.edu/neco/article/35/3/277/112379/Feelings-Are-the-Source-of-Consciousness
mraginskypapers to-read neuroscience cognitionhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:6ba7c1caaa70/[2104.01489] Explanatory models in neuroscience: Part 2 -- constraint-based intelligibility2026-03-04T22:42:22+00:00
https://arxiv.org/abs/2104.01489
mraginskypapers to-read neurosciencehttps://pinboard.in/https://pinboard.in/u:mraginsky/b:a5a0c4e93864/[2104.01490] Explanatory models in neuroscience: Part 1 -- taking mechanistic abstraction seriously2026-03-04T22:41:58+00:00
https://arxiv.org/abs/2104.01490
mraginskypapers to-read neurosciencehttps://pinboard.in/https://pinboard.in/u:mraginsky/b:a4cbe2094f06/[2602.23268] The selfish ribosome2026-03-04T19:58:55+00:00
https://arxiv.org/abs/2602.23268
mraginskypapers to-read biologyhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:458e18545cd4/[2602.24083] Neural Diffusion Intensity Models for Point Process Data2026-03-03T17:42:33+00:00
https://arxiv.org/abs/2602.24083
mraginskypapers to-read diffusions point-processes generative-models neural-networkshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:1b6c3bd2bc9c/AI, Human Cognition and Knowledge Collapse (Daron Acemoglu, Dingwen Kong, Asuman Ozdaglar)2026-03-03T15:19:16+00:00
https://economics.mit.edu/sites/default/files/2026-02/AI%2C%20Human%20Cognition%20and%20Knowledge%20Collapse%2002-20-26.pdf
mraginskypapers to-read economics decision-making aihttps://pinboard.in/https://pinboard.in/u:mraginsky/b:ec1b7439f4e7/Feynman's Ratchet and Pawl | Journal of Statistical Physics | Springer Nature Link2026-03-02T01:40:25+00:00
https://link.springer.com/article/10.1023/B:JOSS.0000033245.43421.14
mraginskypapers to-read thermodynamics statistical-physics stochastic-thermodynamicshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:4410250fda4b/[2602.22271] Support Tokens, Stability Margins, and a New Foundation for Robust LLMs2026-02-27T03:36:04+00:00
https://arxiv.org/abs/2602.22271
mraginskypapers to-read large-language-models transformers stochastic-processeshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:863fccab184b/A philosopher's view of the long road from RCTs to effectiveness - The Lancet2026-01-09T15:29:39+00:00
https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(11)60563-1/fulltext?wptouch_preview_theme=enabled
mraginskypapers to-read philosophy-of-science statistics policyhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:7fff32228f1f/The Logic of Life | Discover Life2026-01-08T21:32:48+00:00
https://link.springer.com/article/10.1007/s11084-016-9494-1
mraginskypapers to-read biology evolution physics thermodynamics statistical-physicshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:2248c2f5d970/[2512.24999] Basic Inequalities for First-Order Optimization with Applications to Statistical Risk Analysis2026-01-06T17:04:39+00:00
https://arxiv.org/abs/2512.24999
mraginskypapers to-read statistics statistical-learning optimizationhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:5ee3b8230fe6/[2512.24945] Dynamic response phenotypes and model discrimination in systems and synthetic biology2026-01-06T03:50:39+00:00
https://arxiv.org/abs/2512.24945
mraginskypapers to-read systems-biology control-theory dynamical-systemshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:dbf668c42dc8/For Differential Equations with r Parameters, 2r+1 Experiments Are Enough for Identification | Journal of Nonlinear Science2025-11-14T03:26:20+00:00
https://link.springer.com/article/10.1007/s00332-002-0506-0
mraginskypapers to-read dynamical-systems differential-equations system-identificationhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:cb57577cf584/How to Lie with (Political) Statistics - Boston Review2025-11-05T16:02:55+00:00
https://www.bostonreview.net/articles/how-to-lie-with-political-statistics/
mraginskyto-read statistics politics data-analysishttps://pinboard.in/https://pinboard.in/u:mraginsky/b:de5bdbd84c17/[2510.15511] Language Models are Injective and Hence Invertible2025-11-05T16:01:19+00:00
https://arxiv.org/abs/2510.15511
mraginskypapers to-read large-language-models dynamical-systems neural-networkshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:b44b817515cc/[2508.11990] Universal Learning of Nonlinear Dynamics2025-10-22T16:19:25+00:00
https://arxiv.org/abs/2508.11990
mraginskypapers to-read system-identification control-theory learning-theory dynamical-systemshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:9164da4f209d/The Symplectic Semigroup and Riccati Differential Equations | Journal of Dynamical and Control Systems2025-10-15T15:41:07+00:00
https://link.springer.com/article/10.1007/s10450-006-9683-8
mraginskypapers to-read dynamical-systems control-theory differential-equations symplectic-geometryhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:adfbeaa3393e/Balancing games - ScienceDirect2025-10-04T17:25:07+00:00
https://www.sciencedirect.com/science/article/pii/0095895677900570
mraginskypapers to-read game-theory geometry optimizationhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:d079fe4b582d/[2509.19601] Modular Machine Learning with Applications to Genetic Circuit Composition2025-09-29T01:53:44+00:00
https://arxiv.org/abs/2509.19601
mraginskypapers to-read systems-biology control-theory dynamical-systemshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:cd5e939dcbbb/Precise Asymptotic Analysis of Deep Random Feature Models2025-09-25T14:13:27+00:00
https://proceedings.mlr.press/v195/bosch23a.html
mraginskypapers to-read machine-learning probability random-matriceshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:d2c36fdb39a5/[2209.08832] From microscopic to macroscopic scale equations: mean field, hydrodynamic and graph limits2025-09-25T13:36:29+00:00
https://arxiv.org/abs/2209.08832
mraginskypapers to-read statistical-physics dynamical-systems interacting-particle-systemshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:b2fd1757e956/Asymptotic theory of in-context learning by linear attention | PNAS2025-09-25T13:34:23+00:00
https://www.pnas.org/doi/full/10.1073/pnas.2502599122
mraginskypapers to-read transformers machine-learning neural-networkshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:2ca76927ce32/[2301.10414] Towards a Unification of Logic and Information Theory2025-09-17T21:27:23+00:00
https://arxiv.org/abs/2301.10414
mraginskypapers to-read information-theory logic formal-methodshttps://pinboard.in/https://pinboard.in/u:mraginsky/b:463dce340e59/Bergsonism in Russia: The case of Bakhtin | Neophilologus2025-09-04T19:05:03+00:00
https://link.springer.com/article/10.1007/BF00212098
mraginskypapers to-read philosophy history_of_ideas via:_onionesquehttps://pinboard.in/https://pinboard.in/u:mraginsky/b:f63e5d35035a/[2508.05776] Whither symbols in the era of advanced neural networks?2025-08-29T14:15:06+00:00
https://arxiv.org/abs/2508.05776
mraginskypapers to-read ai large-language-models cognitive-sciencehttps://pinboard.in/https://pinboard.in/u:mraginsky/b:a55868592f48/[2010.11929] An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale2025-08-24T17:45:28+00:00
https://arxiv.org/abs/2010.11929
mraginskypapers to-read deep-learning computer-vision transformers neural-networks machine-learninghttps://pinboard.in/https://pinboard.in/u:mraginsky/b:c7da9245f8ce/The sovereign individual and the paradox of the digital age | Aeon Essays2025-08-24T17:44:21+00:00
https://aeon.co/essays/the-sovereign-individual-and-the-paradox-of-the-digital-age
mraginskyto-read ai algorithms computation economics capital decision-makinghttps://pinboard.in/https://pinboard.in/u:mraginsky/b:31de9a14c266/[2302.10488] The informativity approach to data-driven analysis and control2025-08-24T17:41:38+00:00
https://arxiv.org/abs/2302.10488
mraginskypapers to-read control-theory behavioral-control data-driven-controlhttps://pinboard.in/https://pinboard.in/u:mraginsky/b:ca74e0e3ac7a/