Pinboard (mraginsky) https://pinboard.in/u:mraginsky/public/ recent bookmarks from mraginsky It’s not the thought that counts: Allostasis at the core of brain function: Neuron 2026-06-02T23:33:52+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 mraginsky papers to-read neuroscience control-theory dynamical-systems cognition https://pinboard.in/ https://pinboard.in/u:mraginsky/b:0eecd28934b3/ The future of control - ScienceDirect 2026-05-05T18:12:23+00:00 https://www.sciencedirect.com/science/article/pii/000510987790022X mraginsky to-read control-theory engineering complex-systems computation https://pinboard.in/ https://pinboard.in/u:mraginsky/b:5c08fa3aa2c7/ STRUCTURES Blog | Predicting the Future: From Cave Paintings to DynaMix 2026-04-18T21:18:09+00:00 https://structures.uni-heidelberg.de/blog/posts/2026_02/ mraginskyblogs dynamical-systems control-theory time-series neural-networks https://pinboard.in/ https://pinboard.in/u:mraginsky/b:02e81ead7f43/ [2512.24945] Dynamic response phenotypes and model discrimination in systems and synthetic biology 2026-01-06T03:50:39+00:00 https://arxiv.org/abs/2512.24945 mraginsky papers to-read systems-biology control-theory dynamical-systems https://pinboard.in/ https://pinboard.in/u:mraginsky/b:dbf668c42dc8/ [2508.11990] Universal Learning of Nonlinear Dynamics 2025-10-22T16:19:25+00:00 https://arxiv.org/abs/2508.11990 mraginsky papers to-read system-identification control-theory learning-theory dynamical-systems https://pinboard.in/ https://pinboard.in/u:mraginsky/b:9164da4f209d/ The Symplectic Semigroup and Riccati Differential Equations | Journal of Dynamical and Control Systems 2025-10-15T15:41:07+00:00 https://link.springer.com/article/10.1007/s10450-006-9683-8 mraginsky papers to-read dynamical-systems control-theory differential-equations symplectic-geometry https://pinboard.in/ https://pinboard.in/u:mraginsky/b:adfbeaa3393e/ [2509.19601] Modular Machine Learning with Applications to Genetic Circuit Composition 2025-09-29T01:53:44+00:00 https://arxiv.org/abs/2509.19601 mraginsky papers to-read systems-biology control-theory dynamical-systems https://pinboard.in/ https://pinboard.in/u:mraginsky/b:cd5e939dcbbb/ [2302.10488] The informativity approach to data-driven analysis and control 2025-08-24T17:41:38+00:00 https://arxiv.org/abs/2302.10488 mraginsky papers to-read control-theory behavioral-control data-driven-control https://pinboard.in/ https://pinboard.in/u:mraginsky/b:ca74e0e3ac7a/ [2501.02267] Towards a constructive framework for control theory 2025-01-07T03:34:13+00:00 https://arxiv.org/abs/2501.02267 mraginsky papers to-read control-theory constructivism optimization https://pinboard.in/ https://pinboard.in/u:mraginsky/b:82cd11b28fee/ Optimal interpolating and smoothing functional artificial neural networks (FANNs) based on a generalized fock space framework | Circuits, Systems, and Signal Processing 2024-12-27T14:03:53+00:00 https://link.springer.com/article/10.1007/BF01202856 mraginsky papers to-read neural-networks nonlinear-systems dynamical-systems control-theory filtering https://pinboard.in/ https://pinboard.in/u:mraginsky/b:05c0de74bb6d/ [2412.07438] Flows of vector fields and the Kalman Theorem 2024-12-15T21:09:53+00:00 https://arxiv.org/abs/2412.07438 mraginsky papers to-read control-theory dynamical-systems differential-geometry https://pinboard.in/ https://pinboard.in/u:mraginsky/b:0a41e9ddec66/ [1512.08055] A Mathematical Theory of Co-Design 2024-11-20T02:13:43+00:00 https://arxiv.org/abs/1512.08055 mraginsky papers to-read categories control-theory systems optimization complex-systems https://pinboard.in/ https://pinboard.in/u:mraginsky/b:0b9bf9fb26dc/ [2305.17628] Convex operator-theoretic methods in stochastic control 2024-08-20T11:05:16+00:00 https://arxiv.org/abs/2305.17628 mraginsky papers to-read control-theory dynamical-systems optimization functional-analysis https://pinboard.in/ https://pinboard.in/u:mraginsky/b:c36d6ed9e02d/ [2304.03519] Robust data-driven control for nonlinear systems using the Koopman operator 2024-08-20T10:58:37+00:00 https://arxiv.org/abs/2304.03519 mraginsky papers to-read control-theory dynamical-systems Koopman-operators https://pinboard.in/ https://pinboard.in/u:mraginsky/b:1b6cb0cfd335/ [2404.18380] Dynamic Global Feedback Stabilization: why do the twist? 2024-08-13T20:11:02+00:00 https://arxiv.org/abs/2404.18380 mraginsky papers to-read control-theory dynamical-systems feedback geometry topology https://pinboard.in/ https://pinboard.in/u:mraginsky/b:1e6f0dfe9c79/ Control Using Logic-Based Switching | SpringerLink 2024-08-12T18:51:27+00:00 https://link.springer.com/book/10.1007/BFb0036078 mraginsky books control-theory adaptive-systems dynamical-systems https://pinboard.in/ https://pinboard.in/u:mraginsky/b:a31bfff8e73a/ The neuron as a direct data-driven controller | PNAS 2024-06-25T02:10:00+00:00 https://www.pnas.org/doi/10.1073/pnas.2311893121 mraginsky papers to-read neuroscience control-theory dynamical-systems https://pinboard.in/ https://pinboard.in/u:mraginsky/b:0fe5a5c7ec9e/ Formalising the role of behaviour in neuroscience - Piantadosi - European Journal of Neuroscience - Wiley Online Library 2024-06-17T19:59:17+00:00 https://onlinelibrary.wiley.com/doi/10.1111/ejn.16372 mraginsky papers to-read neuroscience control-theory dynamical-systems state-space-models https://pinboard.in/ https://pinboard.in/u:mraginsky/b:b2dcbfcf9013/ [2401.14029] Towards a Systems Theory of Algorithms 2024-01-26T03:06:17+00:00 https://arxiv.org/abs/2401.14029 mraginsky papers to-read control-theory algorithms computation learning optimization https://pinboard.in/ https://pinboard.in/u:mraginsky/b:3cf791653c0d/ Feedback Maximum Principle for Ensemble Control of Local Continuity Equations: An Application to Supervised Machine Learning | IEEE Journals & Magazine | IEEE Xplore 2024-01-14T21:02:13+00:00 https://ieeexplore.ieee.org/abstract/document/9454440 mraginsky papers to-read dynamical-systems control-theory ODEs machine-learning https://pinboard.in/ https://pinboard.in/u:mraginsky/b:2028fc5e7330/ [2312.12903] A Minimal Control Family of Dynamical Syetem for Universal Approximation 2023-12-23T20:19:04+00:00 https://arxiv.org/abs/2312.12903 mraginsky papers to-read neural-networks dynamical-systems differential-equations control-theory https://pinboard.in/ https://pinboard.in/u:mraginsky/b:f238f721525e/ [2008.05166] The Mathematical Foundations of Physical Systems Modeling Languages 2023-10-14T15:37:48+00:00 https://arxiv.org/abs/2008.05166 mraginsky papers to-read formal-methods systems control-theory programming-languages https://pinboard.in/ https://pinboard.in/u:mraginsky/b:b40e1216af7b/ Non-Gaussian properties of the real industrial control error in SISO loops | IEEE Conference Publication | IEEE Xplore 2023-10-14T15:16:05+00:00 https://ieeexplore.ieee.org/document/7321405 mraginsky papers to-read control-theory philosophy-of-engineering systems https://pinboard.in/ https://pinboard.in/u:mraginsky/b:fa9ab30c0cbc/ Workshop on Statistical Physics of Inference and Control Theory, Granada 2012 - VideoLectures - VideoLectures.NET 2023-08-09T21:01:56+00:00 http://videolectures.net/cyberstat2012_granada/ mraginskystatistical-physics inference information control-theory learning dynamical-systems https://pinboard.in/ https://pinboard.in/u:mraginsky/b:030cd6bd49c8/ Controllability, integrability and ergodicity | SpringerLink 2023-07-13T21:43:09+00:00 https://link.springer.com/chapter/10.1007/3-540-36589-3_17 mraginsky papers to-read control-theory dynamical-systems ergodic-theory https://pinboard.in/ https://pinboard.in/u:mraginsky/b:25c08d304c7f/ Markovian Representation of Stochastic Processes by Canonical Variables | SIAM Journal on Control and Optimization 2023-07-06T16:01:33+00:00 https://epubs.siam.org/doi/abs/10.1137/0313010?mobileUi=0 mraginsky papers to-read stochastic-processes control-theory https://pinboard.in/ https://pinboard.in/u:mraginsky/b:c20c9638197d/ On strong anticipation - ScienceDirect 2023-05-04T16:41:49+00:00 https://www.sciencedirect.com/science/article/abs/pii/S1389041709000163?casa_token=8dkZ1O1iNBcAAAAA:gnuocqU5jszqBuwnBv1BYYua466pUhmQXOokW-3DOCA_-v5GNHpSCvptgCXuxYcYizauW6_Qzt8 mraginsky papers to-read control-theory dynamical-systems ecological-psychology cognitive-science https://pinboard.in/ https://pinboard.in/u:mraginsky/b:a614ef1065ba/ Dynamical Systems and Sheaves | SpringerLink 2022-10-03T02:57:57+00:00 https://link.springer.com/article/10.1007/s10485-019-09565-x mraginsky to-read type-theory control-theory categories dynamical-systems functional-programming logic papers https://pinboard.in/ https://pinboard.in/u:mraginsky/b:3ee6ce48d6c5/ [1710.10258] Temporal Type Theory: A topos-theoretic approach to systems and behavior 2022-10-03T02:50:36+00:00 https://arxiv.org/abs/1710.10258 mraginsky books to-read type-theory control-theory categories dynamical-systems functional-programming logic https://pinboard.in/ https://pinboard.in/u:mraginsky/b:66d37e1343ca/ The Synergy Between Neuroscience and Control Theory: The Nervous System as Inspiration for Hard Control Challenges | Annual Review of Control, Robotics, and Autonomous Systems 2022-08-23T16:16:04+00:00 https://www.annualreviews.org/doi/full/10.1146/annurev-control-060117-104856 mraginsky papers to-read control-theory neuroscience robotics https://pinboard.in/ https://pinboard.in/u:mraginsky/b:b018fd3772d0/ [1506.03409] Bellman partial differential equation and the hill property for classical isoperimetric problems 2022-08-20T15:04:48+00:00 https://arxiv.org/abs/1506.03409 mraginsky papers to-read isoperimetry probability measure-concentration PDEs control-theory https://pinboard.in/ https://pinboard.in/u:mraginsky/b:06fc15f4dfbf/ [1511.06895] Isoperimetric functional inequalities via the maximum principle: the exterior differential systems approach 2022-08-20T15:04:00+00:00 https://arxiv.org/abs/1511.06895 mraginsky papers to-read isoperimetry probability measure-concentration PDEs control-theory differential-geometry https://pinboard.in/ https://pinboard.in/u:mraginsky/b:8327effc188e/ EUDML  |  Some optimal control applications of real-analytic stratifications and desingularization 2022-08-02T16:25:50+00:00 https://eudml.org/doc/208885 mraginskypapers to-read geometry control-theory dynamical-systems https://pinboard.in/ https://pinboard.in/u:mraginsky/b:8b178b043c07/ [2202.00817] Do Differentiable Simulators Give Better Policy Gradients? 2022-08-02T16:06:50+00:00 https://arxiv.org/abs/2202.00817 mraginsky papers to-read control-theory machine-learning deep-learning simulation reinforcement-learning https://pinboard.in/ https://pinboard.in/u:mraginsky/b:7231e2b55f3d/ The algorithmic origins of life | Journal of The Royal Society Interface 2022-08-02T16:00:01+00:00 https://royalsocietypublishing.org/doi/10.1098/rsif.2012.0869 mraginsky papers to-read biogenesis information-theory algorithms causality control-theory dynamical-systems cybernetics https://pinboard.in/ https://pinboard.in/u:mraginsky/b:053e8aa6fdff/ [2205.09241] Neural ODE Control for Trajectory Approximation of Continuity Equation 2022-05-23T15:18:53+00:00 https://arxiv.org/abs/2205.09241 mraginsky papers to-read control-theory dynamical-systems ODEs SDEs neural-networks machine-learning https://pinboard.in/ https://pinboard.in/u:mraginsky/b:0389d5764128/ Approximate Information State for Approximate Planning and Reinforcement Learning in Partially Observed Systems 2022-03-24T19:51:42+00:00 https://www.jmlr.org/papers/v23/20-1165.html mraginsky papers to-read reinforcement-learning dynamic-programming control-theory heard-the-talk https://pinboard.in/ https://pinboard.in/u:mraginsky/b:50e2a0f7f6dd/ [2101.12606] Dissipativity and optimal control 2022-03-22T20:14:20+00:00 https://arxiv.org/abs/2101.12606 mraginsky papers to-read optimization control-theory dynamical-systems https://pinboard.in/ https://pinboard.in/u:mraginsky/b:2e7dcf0b4bf5/ [2104.05278] Neural ODE control for classification, approximation and transport 2021-07-14T17:31:29+00:00 https://arxiv.org/abs/2104.05278 mraginsky papers to-read neural-networks ODEs dynamical-systems control-theory https://pinboard.in/ https://pinboard.in/u:mraginsky/b:5bafc70f1ac0/ [2006.10330] A Shooting Formulation of Deep Learning 2021-05-03T22:22:04+00:00 https://arxiv.org/abs/2006.10330 mraginsky papers to-read machine-learning neural-networks ODEs control-theory dynamical-systems https://pinboard.in/ https://pinboard.in/u:mraginsky/b:6f5ab0d954eb/ Fundamental bounds on learning performance in neural circuits | PNAS 2021-04-14T15:36:43+00:00 https://www.pnas.org/content/116/21/10537 mraginsky papers to-read neuroscience neural-networks learning control-theory dynamical-systems biology https://pinboard.in/ https://pinboard.in/u:mraginsky/b:05d5179c4894/ A Theory of the Epigenesis of Neuronal Networks by Selective Stabilization of Synapses | PNAS 2021-04-14T15:13:41+00:00 https://www.pnas.org/content/70/10/2974 mraginsky papers to-read neuroscience biology learning control-theory dynamical-systems neural-networks https://pinboard.in/ https://pinboard.in/u:mraginsky/b:0715924cac17/ Frontiers | Homeostasis: The Underappreciated and Far Too Often Ignored Central Organizing Principle of Physiology | Physiology 2021-01-02T02:48:56+00:00 https://www.frontiersin.org/articles/10.3389/fphys.2020.00200/full mraginsky to-read papers cybernetics physiology biology control-theory dynamical-systems https://pinboard.in/ https://pinboard.in/u:mraginsky/b:70dfcf02ea25/ [2007.06007] Universal Approximation Power of Deep Neural Networks via Nonlinear Control Theory 2020-08-19T18:45:41+00:00 https://arxiv.org/abs/2007.06007 mraginsky papers to-read deep-learning neural-networks dynamical-systems control-theory differential-equations https://pinboard.in/ https://pinboard.in/u:mraginsky/b:50632fd10d08/ [2006.06462] Deep Differential System Stability -- Learning advanced computations from examples 2020-07-20T20:17:00+00:00 https://arxiv.org/abs/2006.06462 mraginsky papers to-read machine-learning deep-learning dynamical-systems control-theory state-space-models stability https://pinboard.in/ https://pinboard.in/u:mraginsky/b:ca3ba9610638/ Paths Ahead in the Science of Information and Decision Systems 2020-07-20T19:49:49+00:00 http://paths.lids.mit.edu/ mraginskyconferences control-theory dynamical-systems machine-learning signal-processing systems https://pinboard.in/ https://pinboard.in/u:mraginsky/b:57ab36d14bb4/ The Behavioral Approach to Systems Theory | The n-Category Café 2020-05-22T04:29:18+00:00 https://golem.ph.utexas.edu/category/2018/06/the_behavioral_approach_to_sys.html mraginskysystems control-theory behavioral-control categories https://pinboard.in/ https://pinboard.in/u:mraginsky/b:e19b3b244090/ [1910.13886] Risk bounds for reservoir computing 2019-11-07T03:47:54+00:00 https://arxiv.org/abs/1910.13886 mraginsky papers to-read reservoir-computing filtering control-theory neural-networks dynamical-systems https://pinboard.in/ https://pinboard.in/u:mraginsky/b:21299680593a/ Optimization and Control 2018-10-11T02:14:55+00:00 http://www.statslab.cam.ac.uk/~rrw1/oc/ mraginsky teaching lecture-notes reference control-theory optimization https://pinboard.in/ https://pinboard.in/u:mraginsky/b:6745fd474959/ Intelligent control through learning and optimization (AMATH/CSE 579) 2018-10-11T02:14:21+00:00 https://homes.cs.washington.edu/~todorov/courses/amath579/ mraginsky teaching lecture-notes reference control-theory optimization https://pinboard.in/ https://pinboard.in/u:mraginsky/b:72a77bbee2ad/ Generalized neural network for nonsmooth nonlinear programming problems - IEEE Journals & Magazine 2018-08-09T20:34:37+00:00 https://ieeexplore.ieee.org/document/1333224/ mraginsky papers to-read neural-networks optimization dynamical-systems control-theory stability https://pinboard.in/ https://pinboard.in/u:mraginsky/b:336f075c4fbb/ [1806.05722] Non-asymptotic Identification of LTI Systems from a Single Trajectory 2018-06-18T21:36:27+00:00 https://arxiv.org/abs/1806.05722 mraginsky papers to-read system-identification control-theory https://pinboard.in/ https://pinboard.in/u:mraginsky/b:75a64647a22d/ А. В. Буцев, А. А. Первозванский, “Локальная аппроксимация на искусственных нейросетях”, Автомат. и телемех., 1995, № 9, 127–136; Autom. Remote Control, 56:9 2017-04-14T02:11:05+00:00 http://www.mathnet.ru/php/archive.phtml?wshow=paper&jrnid=at&paperid=3712&option_lang=rus mraginskypapers to-read neural-networks control-theory dynamical-systems https://pinboard.in/ https://pinboard.in/u:mraginsky/b:15787e314d38/ Information, Control, and Learning – The Ingredients of Intelligent Behavior - YouTube 2017-04-04T02:08:08+00:00 https://www.youtube.com/playlist?list=PLYq7WW565SZhPcf5PxsuBUz2PtB7Kfb5X mraginskyinformation-theory machine-learning ai conferences control-theory https://pinboard.in/ https://pinboard.in/u:mraginsky/b:435fae84aea1/ Settable Systems: An Extension of Pearl's Causal Model with Optimization, Equilibrium, and Learning 2017-03-22T15:56:32+00:00 http://www.jmlr.org/papers/v10/white09a.html mraginsky papers to-read causality control-theory https://pinboard.in/ https://pinboard.in/u:mraginsky/b:113d7c9fda33/ [1703.01670] Control Interpretations for First-Order Optimization Methods 2017-03-08T04:40:33+00:00 https://arxiv.org/abs/1703.01670 mraginsky papers optimization control-theory have-read https://pinboard.in/ https://pinboard.in/u:mraginsky/b:b3310a5bc067/ [1611.02635] A Lyapunov Analysis of Momentum Methods in Optimization 2016-11-23T05:27:12+00:00 https://arxiv.org/abs/1611.02635 mraginsky papers to-read optimization dynamical-systems control-theory https://pinboard.in/ https://pinboard.in/u:mraginsky/b:313a13a0954c/ [1607.06494] Stochastic Control via Entropy Compression 2016-07-25T00:47:49+00:00 http://arxiv.org/abs/1607.06494 mraginsky papers to-read control-theory Markov-decision-processes information-theory https://pinboard.in/ https://pinboard.in/u:mraginsky/b:8e90a8909489/ [1510.04214] LQG Control with Minimal Information: Three-Stage Separation Principle and SDP-based Solution Synthesis 2015-10-15T03:08:47+00:00 http://arxiv.org/abs/1510.04214 mraginsky papers to-read information-theory control-theory rational-inattention filtering estimation https://pinboard.in/ https://pinboard.in/u:mraginsky/b:268e8ef145e7/ [1405.6881] Categories in Control 2015-06-28T03:52:01+00:00 http://arxiv.org/abs/1405.6881 mraginsky papers to-read categories control-theory https://pinboard.in/ https://pinboard.in/u:mraginsky/b:39266b4a2702/ [1408.3595] Analysis and Design of Optimization Algorithms via Integral Quadratic Constraints 2014-08-19T03:28:02+00:00 http://arxiv.org/abs/1408.3595 mraginsky papers to-read optimization control-theory dynamical-systems semidefinite-programming https://pinboard.in/ https://pinboard.in/u:mraginsky/b:2cd785e3b2a0/ [1311.5918] Empirical Dynamic Programming 2013-12-02T01:23:26+00:00 http://arxiv.org/abs/1311.5918 mraginsky papers to-read dynamic-programming control-theory Markov-decision-processes https://pinboard.in/ https://pinboard.in/u:mraginsky/b:344b48f7cf85/ [1203.1429] Probabilistic Optimal Estimation and Filtering under Uncertainty 2013-10-24T01:01:34+00:00 http://arxiv.org/abs/1203.1429 mraginskypapers to-read control-theory estimation system-identification complexity adaptive-systems https://pinboard.in/ https://pinboard.in/u:mraginsky/b:d9b31a46e283/ Publications: Harvard Robotics Laboratory 2013-10-09T02:24:31+00:00 http://hrl.harvard.edu/publications/ mraginskypapers control-theory robotics dynamical-systems differential-geometry https://pinboard.in/ https://pinboard.in/u:mraginsky/b:b0c259724979/ Efficient Reinforcement Learning for High Dimensional Linear Quadratic Systems (NIPS 2012) 2013-01-21T01:14:17+00:00 http://books.nips.cc/papers/files/nips25/bibhtml/NIPS2012_1237.html mraginskypapers to-read adaptive-systems control-theory re:adaptive_control_project https://pinboard.in/ https://pinboard.in/u:mraginsky/b:3eae0b85976a/ Professor Eugene A. Feinberg 2012-08-17T21:12:20+00:00 http://www.ams.sunysb.edu/~feinberg/ mraginskypeople homepages papers research control-theory https://pinboard.in/ https://pinboard.in/u:mraginsky/b:754e6d18e512/ [1204.5721] Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems 2012-04-27T18:20:30+00:00 http://arxiv.org/abs/1204.5721 mraginsky papers to-read bandit-problems online-learning control-theory dynamic-programming decision-making https://pinboard.in/ https://pinboard.in/u:mraginsky/b:11d540786e36/ "Approximate dynamic programming via Bellman inequalities" (Wang and Boyd) 2012-04-17T02:12:37+00:00 http://www.stanford.edu/~boyd/papers/pdf/adp_iter_bellman.pdf mraginsky papers to-read control-theory dynamic-programming optimization https://pinboard.in/ https://pinboard.in/u:mraginsky/b:b0771149d366/ [1203.4626] Active Sequential Hypothesis Testing 2012-03-22T00:38:37+00:00 http://arxiv.org/abs/1203.4626 mraginsky papers to-read control-theory information-theory adaptive-systems heard-the-talk https://pinboard.in/ https://pinboard.in/u:mraginsky/b:f4add78bdb48/ Certainty equivalence and model uncertainty 2012-02-25T16:23:11+00:00 http://ideas.repec.org/a/fip/fedgpr/y2005p17-38.html mraginsky papers to-read adaptive-systems control-theory dynamic-programming estimation game-theory uncertainty https://pinboard.in/ https://pinboard.in/u:mraginsky/b:d06e26b7fc8e/