https://pinboard.in/u:cshalizi/public/ recent bookmarks from cshalizi 2026-06-01T13:58:12+00:00 https://www.jstor.org/stable/1403785?seq=1 cshaliziin_NB markov_models history_of_mathematics markov.a.a. ergodic_theory mixing free_will https://pinboard.in/ https://pinboard.in/u:cshalizi/b:b76b51010206/ 2026-01-27T03:26:30+00:00 https://arxiv.org/abs/2512.15605 cshalizi to:NB large_language_models_(so_called) gibbs_distributions random_fields markov_models https://pinboard.in/ https://pinboard.in/u:cshalizi/b:00b414131396/ 2025-12-18T02:50:13+00:00 https://www.pnas.org/doi/10.1073/pnas.2411731121 cshalizi to:NB non-equilibrium self-organization statistical_mechanics stochastic_processes markov_models randall.dana to_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:1730b51f604e/ 2025-11-20T20:42:22+00:00 https://link.springer.com/article/10.1007/s10955-025-03528-4 cshalizi to:NB physics non-equilibrium information_geometry markov_models stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:996c6add6ce2/ 2025-09-02T02:49:02+00:00 https://arxiv.org/abs/2508.21055 cshalizi to:NB to_read markov_models stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:4b52c6b91f38/ 2025-08-08T03:11:31+00:00 https://link.springer.com/article/10.1007/BF01295322 cshalizi to:NB have_read sofic_processes symbolic_dynamics dynamical_systems markov_models automata_theory https://pinboard.in/ https://pinboard.in/u:cshalizi/b:e99618a1664e/ 2025-07-08T15:28:11+00:00 https://link.springer.com/article/10.1007/s10955-025-03453-6 cshalizi in_NB markov_models ergodic_theory chemistry https://pinboard.in/ https://pinboard.in/u:cshalizi/b:47b10b880d00/ 2025-02-03T00:40:20+00:00 https://arxiv.org/abs/2410.02724 cshalizi0$. Thus every length $T$ context is followed by any other context of length $T$ with a minimum probability of $c^T>0$. Hence, taking successive length-$T$ blocks of symbols as the states, the chain is plainly aperiodic and recurrent. Moreover, for any distributions f and g over such states, $d(Qf, Qg) \leq d(f,g)$ because $Qf$ and $Qg$ include at least a minimum amount of smearing out over everything, and now we're off. (I haven't tried to bound the convergence rate this way but it's plainly do-able if I re-read Fogel, or Latosa and Mackey.) --- ETA: On thinking about this further, the coupling method is probably a better way. Consider the chain on $X^2$ where each component independently follows the transition matrix $Q$, until the two coordinates hit the same state at once, and then their trajectories merge. Let $M$ be the time of merger. It's a familiar result that d(Q^k f, Q^k g) \leq Pr(M > k). Now there, in this situation, with $K$ symbol types and a context window of length $T$, there are $K^T$ states where we could merge, the probability of the two block chains hitting the same state after one step, $k=1$, is clearly at least $c^{2T}$, and there are $K^T$ such states, so the probability of merger after one step is at least $(Kc^2)^T$. So the probability of _not_ merging in one step is at most $1-(Kc^2)^T$, i.e., $Pr(M>1) \leq 1-(K c^2)^T$. Similarly $Pr(M>2) \leq (1-(K c^2)^T)^2$, since that requires not merging on either the first step _or_ the second, and again the probability of merger at either step is at a minimum $(K c^2)^T$. (Also, we must have $c \leq 1/K$, since $c$ is the minimum probability of producing any of the $K$ symbol types, hence $K c^2 < 1$.) 2. I don't understand how to interpret their in-context theorems at all.]]> markov_models large_language_models_(so_called) in_NB have_read re:large_language_models_in_statistical_perspective https://pinboard.in/ https://pinboard.in/u:cshalizi/b:391fa8dedf0b/ 2024-12-11T16:02:48+00:00 https://arxiv.org/abs/2203.04395 cshalizi to:NB markov_models mixing ergodic_theory re:almost_none https://pinboard.in/ https://pinboard.in/u:cshalizi/b:bb278df058e6/ 2024-08-26T13:47:31+00:00 https://arxiv.org/abs/2102.01938 cshalizi in_NB probability markov_models good-turing https://pinboard.in/ https://pinboard.in/u:cshalizi/b:990dff2666bf/ 2024-08-21T17:39:24+00:00 https://arxiv.org/abs/2407.15277 cshalizi conformal_prediction markov_models in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:045f1fa57489/ 2023-07-25T14:19:26+00:00 https://www.pnas.org/doi/full/10.1073/pnas.180265397 cshalizi to:NB have_read bioinformatics markov_models re:CSSR cleaning_out_the_filing_cabinet_for_the_first_time_since_2005 https://pinboard.in/ https://pinboard.in/u:cshalizi/b:9f1cb062df07/ 2023-05-01T19:57:57+00:00 https://link.springer.com/book/10.1007/3-540-45804-2 cshalizi in_NB markov_models interacting_particle_systems distributed_systems to_read cleaning_out_the_filing_cabinet_for_the_first_time_since_2005 https://pinboard.in/ https://pinboard.in/u:cshalizi/b:8164ee44d88f/ 2023-04-24T21:43:30+00:00 https://doi.org/10.1016/0022-2496(66)90020-4 cshalizi have_read markov_models cognitive_science variable-length_markov_models_aka_context_trees statistical_inference_for_stochastic_processes re:AoS_project cleaning_out_the_filing_cabinet_for_the_first_time_since_2005 re:dissertation prediction in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:851a2a33fb27/ 2022-06-19T17:05:18+00:00 https://arxiv.org/abs/2111.12603 cshalizi central_limit_theorem stochastic_processes convergence_of_stochastic_processes markov_models re:almost_none in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:23ae04823e1b/ 2022-06-12T06:11:55+00:00 https://www.research-collection.ethz.ch/handle/20.500.11850/354751 cshalizistatistical_mechanics non-equilibrium large_deviations stochastic_processes markov_models have_skimmed in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:47e2725ff00f/ 2022-06-10T14:07:30+00:00 https://arxiv.org/abs/2205.13615 cshalizi branching_processes markov_models stochastic_processes in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:0d1c60549638/ 2022-06-09T08:19:32+00:00 https://arxiv.org/abs/2203.04163 cshalizi to:NB stochastic_processes mixing markov_models martingales https://pinboard.in/ https://pinboard.in/u:cshalizi/b:03c6185cd447/ 2021-10-18T13:52:08+00:00 https://arxiv.org/abs/2110.04338 cshalizi to:NB markov_models stochastic_processes learning_theory learning_under_dependence https://pinboard.in/ https://pinboard.in/u:cshalizi/b:784109e439d5/ 2021-08-16T03:26:10+00:00 https://onlinelibrary.wiley.com/doi/abs/10.1111/jtsa.12615 cshalizi to:NB time_series markov_models re:AoS_project statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:dd1ba3024572/ 2021-08-03T04:43:45+00:00 https://arxiv.org/abs/2107.14268 cshalizi to:NB stochastic_processes markov_models statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:310141c80200/ 2021-07-27T12:07:24+00:00 https://arxiv.org/abs/2105.04393 cshalizi markov_models random_matrices color_me_skeptical in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:60c9dcd3891e/ 2021-07-01T13:29:55+00:00 https://arxiv.org/abs/2101.09045 cshalizi to:NB markov_models large_deviations statistical_inference_for_stochastic_processes statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f99b5b88b07a/ 2021-06-30T02:57:36+00:00 https://arxiv.org/abs/2106.13947 cshalizi to:NB prediction time_series mixing markov_models statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:be4dfa48c5ee/ 2021-06-25T14:55:04+00:00 https://arxiv.org/abs/2011.00308 cshalizi to:NB to_read markov_models minimax empirical_processes statistical_inference_for_stochastic_processes re:almost_none mixing statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:60fea291f30b/ 2021-06-10T02:19:56+00:00 https://arxiv.org/abs/1901.08478 cshalizi to:NB large_deviations markov_models non-equilibrium https://pinboard.in/ https://pinboard.in/u:cshalizi/b:a8ebd869f880/ 2021-06-07T03:55:45+00:00 https://arxiv.org/abs/2106.01645 cshalizi to:NB stochastic_processes markov_models state-space_models information_theory https://pinboard.in/ https://pinboard.in/u:cshalizi/b:acea15a6abd1/ 2021-05-30T21:06:34+00:00 https://arxiv.org/abs/2104.05095 cshalizi to:NB stochastic_processes markov_models metastability https://pinboard.in/ https://pinboard.in/u:cshalizi/b:d94fd43cf4ab/ 2021-04-19T14:39:06+00:00 https://arxiv.org/abs/2104.07798 cshalizi to:NB to_read re:AoS_project markov_models latora.vito 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https://pinboard.in/ https://pinboard.in/u:cshalizi/b:0b4d069d0ae8/ 2021-01-22T05:56:38+00:00 https://arxiv.org/abs/1906.03212 cshalizi to:NB markov_models stochastic_processes stochastic_differential_equations metastability kurtz.thomas_g. https://pinboard.in/ https://pinboard.in/u:cshalizi/b:7c7872cc56c0/ 2021-01-19T18:33:59+00:00 https://arxiv.org/abs/2101.06936 cshalizi to:NB markov_models empirical_processes concentration_of_measure stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f9a9a23f65e4/ 2021-01-12T22:39:27+00:00 https://arxiv.org/abs/2101.03801 cshalizi to:NB markov_models state-space_models random_fields statistics_on_manifolds https://pinboard.in/ https://pinboard.in/u:cshalizi/b:b0b4911debdd/ 2021-01-10T19:43:19+00:00 https://onlinelibrary.wiley.com/doi/abs/10.1111/jtsa.12583?campaign=wolacceptedarticle cshalizi to:NB stochastic_processes markov_models mixing https://pinboard.in/ https://pinboard.in/u:cshalizi/b:34be5d457c2b/ 2021-01-07T21:45:47+00:00 https://arxiv.org/abs/2101.02002 cshalizi to:NB stochastic_processes markov_models martingales re:almost_none https://pinboard.in/ https://pinboard.in/u:cshalizi/b:1d920b25cb18/ 2020-12-26T05:31:52+00:00 https://arxiv.org/abs/2012.12917 cshalizi to:NB probability hilbert_space kernel_estimators markov_models https://pinboard.in/ https://pinboard.in/u:cshalizi/b:a69b6cfce1b3/ 2020-12-16T20:18:43+00:00 https://journals.sagepub.com/doi/abs/10.1177/0049124118782541 cshalizi to:NB markov_models stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:cac2b551ff60/ 2020-12-16T17:45:04+00:00 https://arxiv.org/abs/2012.07954 cshalizi to:NB stochastic_processes markov_models compartment_models wiuf.carsten https://pinboard.in/ https://pinboard.in/u:cshalizi/b:16ab5c567d43/ 2020-12-16T14:47:51+00:00 https://sociologicalscience.com/articles-v7-20-487/ cshalizi to:NB markov_models compartment_models dynamics_on_networks to_read color_me_skeptical https://pinboard.in/ https://pinboard.in/u:cshalizi/b:268e76410023/ 2020-12-11T17:26:24+00:00 https://projecteuclid.org/euclid.aos/1607677244 cshalizi to:NB markov_models statistical_inference_for_stochastic_processes clustering statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:7c12332b27bd/ 2020-12-10T05:27:05+00:00 https://arxiv.org/abs/2011.14821 cshalizi to:NB stochastic_processes markov_models prediction prediction_processes hilbert_space kith_and_kin crutchfield.james_p. to_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:ad432232e8fa/ 2020-12-10T04:11:03+00:00 https://arxiv.org/abs/1703.06447 cshalizi to:NB stochastic_processes markov_models large_deviations https://pinboard.in/ https://pinboard.in/u:cshalizi/b:bfbb37e4d404/ 2020-12-07T15:28:12+00:00 https://arxiv.org/abs/2012.02303 cshalizi to:NB distributed_systems control_theory_and_control_engineering markov_models https://pinboard.in/ https://pinboard.in/u:cshalizi/b:043e1290163d/ 2020-12-07T15:18:38+00:00 https://link.springer.com/chapter/10.1007/978-3-030-35902-7_9 cshalizi to:NB to_read markov_models sociology inequality to_teach:data_over_space_and_time rvenkat https://pinboard.in/ https://pinboard.in/u:cshalizi/b:2be4b1b806de/ 2020-12-02T01:46:44+00:00 https://arxiv.org/abs/2011.14994 cshalizi to:NB statistical_mechanics non-equilibrium markov_models https://pinboard.in/ https://pinboard.in/u:cshalizi/b:912c49235927/ 2020-12-02T01:43:04+00:00 https://arxiv.org/abs/2011.14664 cshalizi to:NB stochastic_processes markov_models https://pinboard.in/ https://pinboard.in/u:cshalizi/b:b0f44a064e72/ 2020-11-30T04:02:00+00:00 https://arxiv.org/abs/2011.10985 cshalizi markov_models convergence_of_stochastic_processes stochastic_processes stochastic_differential_equations approximation stochastic_gradient_descent in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:c3a1ccd774e2/ 2020-11-30T03:59:56+00:00 https://arxiv.org/abs/1907.00113 cshalizi to:NB low-rank_approximation markov_models statistics optimization statistical_inference_for_stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:7c5dd99517e8/ 2020-11-30T03:02:09+00:00 https://arxiv.org/abs/2011.13780 cshalizi to:NB markov_models convergence_of_stochastic_processes stochastic_processes re:almost_none approximation https://pinboard.in/ https://pinboard.in/u:cshalizi/b:df4597d34e61/ 2020-11-25T14:36:08+00:00 https://arxiv.org/abs/2005.06623 cshalizi to:NB prediction markov_models time_series to_read macro_from_micro kernel_smoothing https://pinboard.in/ https://pinboard.in/u:cshalizi/b:0145978fda9c/ 2020-11-23T17:42:40+00:00 https://arxiv.org/abs/2002.02001 cshalizi to:NB state-space_models markov_models ecology statistics to_teach:data_over_space_and_time https://pinboard.in/ https://pinboard.in/u:cshalizi/b:176ad5a8bc65/ 2020-11-21T03:45:52+00:00 https://onlinelibrary.wiley.com/doi/full/10.1002/env.1102?casa_token=ocbU79FU42EAAAAA%3AQDyFS0-w-z1X4iyTEguPeij1WKqyFlab8iL4qHNhaVg8STIrrUbdwgliDave2STG6TP7Ue6-ZfbM6g cshalizi 900) and no more than moderate spatial dependence. When the lattice is large enough, and the dependence small enough, to permit reliable inference, the three approaches perform comparably, and so we recommend the PL approach for its easier implementation and much faster execution."]]> to:NB random_fields ecology spatial_statistics birds markov_models ising_model logistic_regression to_teach:data_over_space_and_time of_course_its_really_a_spin_glass have_skimmed https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f06130584e87/ 2020-11-21T03:42:14+00:00 https://link.springer.com/article/10.1198/108571105X46543 cshalizi to:NB spatio-temporal_statistics random_fields markov_models insects have_skimmed to_teach:data_over_space_and_time of_course_its_really_a_spin_glass ising_model logistic_regression https://pinboard.in/ https://pinboard.in/u:cshalizi/b:01152ca5b0a6/ 2020-11-21T03:41:58+00:00 https://link.springer.com/article/10.1023/A:1018553807765 cshalizi to:NB ecology spatial_statistics markov_models random_fields have_skimmed to_teach:data_over_space_and_time of_course_its_really_a_spin_glass ising_model logistic_regression https://pinboard.in/ https://pinboard.in/u:cshalizi/b:1e0bc6629a0a/ 2020-11-20T04:03:29+00:00 https://projecteuclid.org/euclid.bj/1605841254 cshalizi to:NB markov_models statistical_inference_for_stochastic_processes kith_and_kin kontorovich.aryeh https://pinboard.in/ https://pinboard.in/u:cshalizi/b:3b6d2a8bf1e0/ 2020-11-19T05:30:29+00:00 https://projecteuclid.org/euclid.aos/1600480925 cshalizi to:NB hypothesis_testing markov_models stochastic_processes statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:db42efc7de75/ 2020-11-18T21:47:12+00:00 https://projecteuclid.org/euclid.aos/1594972821 cshalizi markov_models stochastic_processes optimization stochastic_gradient_descent in_NB bach.francis https://pinboard.in/ https://pinboard.in/u:cshalizi/b:0a733827e7de/ 2020-11-16T16:02:36+00:00 https://ieeexplore.ieee.org/document/8804216 cshalizi to:NB entropy information_theory markov_models state-space_models doucet.arnaud https://pinboard.in/ https://pinboard.in/u:cshalizi/b:9e84242609c9/ 2020-11-15T21:14:02+00:00 https://arxiv.org/abs/1912.00401 cshalizi to:NB stochastic_processes markov_models biochemical_networks to_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:3c8dfed1a256/ 2020-07-15T15:37:53+00:00 https://arxiv.org/abs/1607.07570 cshalizi to:NB heard_the_talk network_data_analysis markov_models kith_and_kin moore.cristopher newman.mark networks_in_and_over_time https://pinboard.in/ https://pinboard.in/u:cshalizi/b:3e41f2daf2a9/ 2020-05-29T13:38:49+00:00 https://arxiv.org/abs/2005.03750 cshalizi to:NB to_read prediction markov_models statistical_inference_for_stochastic_processes crutchfield.james_p. entropy_estimation https://pinboard.in/ https://pinboard.in/u:cshalizi/b:01310a468c03/ 2020-05-16T17:46:39+00:00 https://www.mdpi.com/1099-4300/11/3/385 cshalizi to:NB complexity_measures markov_models prediction stochastic_processes to_read re:AoS_project https://pinboard.in/ https://pinboard.in/u:cshalizi/b:7bbb0912fe69/ 2020-05-12T23:51:32+00:00 https://www.sciencedirect.com/science/article/abs/pii/S0031320305000233?via%3Dihub cshalizi to:NB markov_models automata_theory to_read re:AoS_project https://pinboard.in/ https://pinboard.in/u:cshalizi/b:4432b2e40b08/ 2020-05-12T23:48:53+00:00 https://arxiv.org/abs/math/0606591 cshalizi to:NB approximation stochastic_processes information_theory markov_models re:AoS_project to_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:7ded2a998ee1/ 2020-05-12T23:48:06+00:00 https://arxiv.org/abs/0912.4480 cshalizi to:NB have_read markov_models statistical_inference_for_stochastic_processes statistics_on_manifolds time_series https://pinboard.in/ https://pinboard.in/u:cshalizi/b:45a70689d38a/ 2020-05-08T17:11:21+00:00 https://epubs.siam.org/doi/abs/10.1137/1035003?casa_token=VQ1U2GEJoAUAAAAA:RWor_QJUmKSrKfuGUlp9flVZPu5RhXtsXYLZYpEK-O-ah6MH27i3zyXrPqw3xrY-oOaRyOtzAME cshalizi to_read markov_models dynamical_systems stochastic_processes simon.carl_p. jacquez.john_a. to_teach:data_over_space_and_time in_NB compartment_models https://pinboard.in/ https://pinboard.in/u:cshalizi/b:ce4faf53ed71/ 2020-01-30T23:52:29+00:00 https://arxiv.org/abs/1911.12198 cshalizi to:NB random_fields markov_models statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:80cc0dfb4787/