Pinboard (cshalizi) https://pinboard.in/u:cshalizi/public/ recent bookmarks from cshalizi [2512.15605] Autoregressive Language Models are Secretly Energy-Based Models: Insights into the Lookahead Capabilities of Next-Token Prediction 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/ Gaussian concentration bounds for probabilistic cellular automata | Journal of Statistical Physics 2025-12-26T14:23:09+00:00 https://link.springer.com/article/10.1007/s10955-025-03552-4 cshalizi to:NB concentration_of_measure random_fields stochastic_processes cellular_automata chazottes.jean-rene https://pinboard.in/ https://pinboard.in/u:cshalizi/b:9f0c1770e032/ The screening effect in Kriging 2023-10-05T01:22:50+00:00 https://projecteuclid.org/journals/annals-of-statistics/volume-30/issue-1/The-screening-effect-in-Kriging/10.1214/aos/1015362194.full cshalizi have_skimmed spatial_statistics random_fields statistics to_teach:data_over_space_and_time in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:eb89cb46ceea/ Uniform Asymptotic Optimality of Linear Predictions of a Random Field Using an Incorrect Second-Order Structure 2023-10-04T20:23:28+00:00 https://projecteuclid.org/journals/annals-of-statistics/volume-18/issue-2/Uniform-Asymptotic-Optimality-of-Linear-Predictions-of-a-Random-Field/10.1214/aos/1176347629.full cshalizispatial_statistics random_fields have_skimmed to_teach:data_over_space_and_time in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:9a75106c9994/ Asymptotically Efficient Prediction of a Random Field with a Misspecified Covariance Function 2023-10-04T20:22:51+00:00 https://projecteuclid.org/journals/annals-of-statistics/volume-16/issue-1/Asymptotically-Efficient-Prediction-of-a-Random-Field-with-a-Misspecified/10.1214/aos/1176350690.full cshalizi spatial_statistics have_skimmed to_teach:data_over_space_and_time random_fields in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:877383588193/ Communication Norms and the Collective Cognitive Performance of “Invisible Colleges” | SpringerLink 2023-05-10T02:44:02+00:00 https://link.springer.com/chapter/10.1007/978-3-662-03738-6_7 cshalizi in_NB collective_cognition sociology_of_science david.paul_a. science_as_a_social_process random_fields voter_model heard_the_talk cleaning_out_the_filing_cabinet_for_the_first_time_since_2005 https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f2dd9bd2f1fb/ [2305.00322] Toward $L_infty$-recovery of Nonlinear Functions: A Polynomial Sample Complexity Bound for Gaussian Random Fields 2023-05-05T01:47:16+00:00 https://arxiv.org/abs/2305.00322 cshalizi approximation learning_theory random_fields in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:fb73aea45ac1/ [2112.01288] How to quantify fields or textures? A guide to the scattering transform 2023-03-21T15:02:11+00:00 https://arxiv.org/abs/2112.01288 cshalizi pattern_recognition spatial_statistics random_fields neural_networks via:mraginsky in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:4b7134f912fc/ Inference Tools for Markov Random Fields on Lattices: The R Package mrf2d | Journal of Statistical Software 2022-06-15T07:49:49+00:00 https://www.jstatsoft.org/article/view/v101i08 cshalizi to:NB random_fields monte_carlo R statistical_inference_for_stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:1a0c75188ebb/ [2206.03769] Renormalization group and generalized Central Limit Theorems: The critical probability distributions of the order parameter of the Ising model 2022-06-09T08:20:19+00:00 https://arxiv.org/abs/2206.03769 cshalizi to:NB stochastic_processes random_fields central_limit_theorem ising_model renormalization https://pinboard.in/ https://pinboard.in/u:cshalizi/b:0ddadeac6846/ [2102.02365] Wind Field Reconstruction with Adaptive Random Fourier Features 2022-04-22T12:29:46+00:00 https://arxiv.org/abs/2102.02365 cshalizi to:NB to_read spatial_statistics smoothing random_fields random_features to_teach:data_over_space_and_time via:? https://pinboard.in/ https://pinboard.in/u:cshalizi/b:28210c4cccd9/ Statistical Estimation from Dependent Data 2021-07-11T16:44:59+00:00 http://proceedings.mlr.press/v139/kandiros21a.html cshalizi to:NB learning_theory random_fields classifiers dependent_learning of_course_its_really_a_spin_glass statistics learning_under_dependence https://pinboard.in/ https://pinboard.in/u:cshalizi/b:a1d41909f983/ [2107.03162] Distance covariance for random fields 2021-07-08T16:30:37+00:00 https://arxiv.org/abs/2107.03162 cshalizi to:NB random_fields dependence_measures https://pinboard.in/ https://pinboard.in/u:cshalizi/b:9ebc13e22e92/ [2106.14145] An Approach to Causal Inference over Stochastic Networks 2021-06-30T02:51:15+00:00 https://arxiv.org/abs/2106.14145 cshalizi to:NB network_data_analysis exponential_family_random_graphs random_fields handcock.mark causal_inference re:homophily_and_confounding statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:1bf3c5d4ff92/ [2005.14458] Distributional Random Forests: Heterogeneity Adjustment and Multivariate Distributional Regression 2021-06-01T17:33:18+00:00 https://arxiv.org/abs/2005.14458 cshalizi to:NB density_estimation random_fields buhlmann.peter ensemble_methods statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:35774f99f672/ [1911.06770] Probabilistic Foundations of Spatial Mean-field Models in Ecology and Applications 2021-05-30T20:44:54+00:00 https://arxiv.org/abs/1911.06770 cshalizi to:NB ecology macro_from_micro random_fields levin.simon https://pinboard.in/ https://pinboard.in/u:cshalizi/b:e6ad02fba8ee/ [2012.09549] Stochastic Lotka-Volterra Competitive Reaction-Diffusion Systems Perturbed by Space-Time White Noise: Modeling and Analysis 2021-05-13T05:24:07+00:00 https://arxiv.org/abs/2012.09549 cshalizi to:NB random_fields ecology stochastic_differential_equations https://pinboard.in/ https://pinboard.in/u:cshalizi/b:022cb07d27b9/ [2007.10874] Central limit theorems for stationary random fields under weak dependence with application to ambit and mixed moving average fields 2021-04-08T14:25:42+00:00 https://arxiv.org/abs/2007.10874 cshalizi to:NB mixing dependence_measures random_fields central_limit_theorem stochastic_processes to_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f6d72975cae5/ [1904.11060] Normal Approximation in Large Network Models 2021-03-03T04:28:29+00:00 https://arxiv.org/abs/1904.11060 cshalizi to:NB network_data_analysis statistics random_fields central_limit_theorem https://pinboard.in/ https://pinboard.in/u:cshalizi/b:4680019e3ec7/ [2101.03801] Hidden Markov chains and fields with observations in Riemannian manifolds 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/ Katzfuss , Guinness : A General Framework for Vecchia Approximations of Gaussian Processes 2020-12-21T14:09:14+00:00 https://projecteuclid.org/euclid.ss/1608541222 cshalizi to:NB approximation computational_statistics random_fields gaussian_processes stochastic_processes statistics_on_manifolds https://pinboard.in/ https://pinboard.in/u:cshalizi/b:21d74c2d020c/ [2005.06371] Nonparametric regression for locally stationary random fields under stochastic sampling design 2020-12-16T17:47:23+00:00 https://arxiv.org/abs/2005.06371 cshalizi to:NB random_fields spatial_statistics spatio-temporal_statistics smoothing nonparametrics regression additive_models statistics to_teach:data_over_space_and_time kernel_smoothing https://pinboard.in/ https://pinboard.in/u:cshalizi/b:9759167da0d4/ [2004.09370] Learning Ising models from one or multiple samples 2020-12-12T19:59:01+00:00 https://arxiv.org/abs/2004.09370 cshalizi to:NB ising_model random_fields statistical_inference_for_stochastic_processes statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:e567bce5885c/ [2012.05784] Detecting Structured Signals in Ising Models 2020-12-12T19:58:07+00:00 https://arxiv.org/abs/2012.05784 cshalizi to:NB ising_model hypothesis_testing random_fields https://pinboard.in/ https://pinboard.in/u:cshalizi/b:aca767ba90f5/ Autologistic models for binary data on a lattice - Hughes - 2011 - Environmetrics - Wiley Online Library 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/ Modeling spatial-temporal binary data using Markov random fields | SpringerLink 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/ Modelling the distribution of plant species using the autologistic regression model | SpringerLink 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/ [2011.09690] Onsager-Machlup action functional for stochastic partial differential equations with Levy noise 2020-11-20T04:02:50+00:00 https://arxiv.org/abs/2011.09690 cshalizi to:NB stochastic_differential_equations stochastic_processes large_deviations to_read random_fields spatio-temporal_statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:c6c4c2511f68/ Testing Ising Models - IEEE Journals & Magazine 2020-11-16T17:00:33+00:00 https://ieeexplore.ieee.org/document/8782628 cshalizi to:NB random_fields hypothesis_testing statistics ising_model https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f131bb3148ca/ A local limit theorem for linear random fields - Fortune - - Journal of Time Series Analysis - Wiley Online Library 2020-09-28T19:27:43+00:00 https://onlinelibrary.wiley.com/doi/abs/10.1111/jtsa.12556 cshalizi to:NB stochastic_processes random_fields https://pinboard.in/ https://pinboard.in/u:cshalizi/b:562fed0a71f2/ [1911.12198] Strong structure recovery for partially observed discrete Markov random fields on graphs 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/ Chen , Wang : Distributional properties and estimation in spatial image clustering 2019-11-25T15:56:21+00:00 https://projecteuclid.org/euclid.ejs/1573009454 cshalizi spatial_statistics random_fields to_teach:data_over_space_and_time statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f86f8219aad8/ [1910.09645] Markov Random Fields for Collaborative Filtering 2019-10-24T13:44:56+00:00 https://arxiv.org/abs/1910.09645 cshalizi to:NB random_fields collaborative_filtering https://pinboard.in/ https://pinboard.in/u:cshalizi/b:6716a868dae4/ [1909.10943] Bounded law of the iterated logarithms for stationary random fields 2019-09-26T03:47:31+00:00 https://arxiv.org/abs/1909.10943 cshalizi to:NB probability stochastic_processes random_fields https://pinboard.in/ https://pinboard.in/u:cshalizi/b:851c02d769e3/ [1909.06401] Fluctuations for Spatially Extended Hawkes Processes 2019-09-18T12:56:35+00:00 https://arxiv.org/abs/1909.06401 cshalizi to:NB point_processes stochastic_processes random_fields central_limit_theorem https://pinboard.in/ https://pinboard.in/u:cshalizi/b:fd12d1a0a806/ [1809.08686] On the quenched CLT for stationary random fields under projective criteria 2019-09-15T14:46:54+00:00 https://arxiv.org/abs/1809.08686 cshalizi to:NB stochastic_processes random_fields martingales central_limit_theorem https://pinboard.in/ https://pinboard.in/u:cshalizi/b:138affc41fd1/ [1909.03238] Linear response and moderate deviations: hierarchical approach. V 2019-09-15T14:29:24+00:00 https://arxiv.org/abs/1909.03238 cshalizi to:NB central_limit_theorem random_fields stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:b61503a99002/ [1908.09177] Dynamics of Stochastic Reaction-Diffusion Equations 2019-08-27T15:30:14+00:00 https://arxiv.org/abs/1908.09177 cshalizi to:NB stochastic_differential_equations random_fields stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:d144e176a371/ [1810.04496] On maxima of stationary fields 2019-08-20T14:52:31+00:00 https://arxiv.org/abs/1810.04496 cshalizivn,MAn≤vn))+o(1), for some increasing sequence of sets An of size o(nd). For a class of fields satisfying a local mixing condition, including m-dependent ones, the theorem holds with a constant finite A replacing An. The above results lead to new formulas for the extremal index for random fields."]]> to:NB extreme_values random_fields stochastic_processes mixing re:almost_none https://pinboard.in/ https://pinboard.in/u:cshalizi/b:b48b11d4a911/ [1907.05414] Variational principle for weakly dependent random fields 2019-08-05T13:12:22+00:00 https://arxiv.org/abs/1907.05414 cshalizi to:NB information_theory random_fields stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:83c995311f8f/ [1905.12554] Extreme value theory of evolving phenomena in complex dynamical systems: firing cascades in a model of neural network 2019-05-30T16:06:44+00:00 https://arxiv.org/abs/1905.12554 cshalizi to:NB extreme_values random_fields dynamical_systems https://pinboard.in/ https://pinboard.in/u:cshalizi/b:1601c5f7fe9b/ The Fokker–Planck Approach to Complex Spatiotemporal Disordered Systems | Annual Review of Condensed Matter Physics 2019-05-26T17:57:18+00:00 https://www.annualreviews.org/doi/abs/10.1146/annurev-conmatphys-033117-054252 cshalizi to:NB stochastic_processes random_fields physics statistical_mechanics markov_models macro_from_micro non-equilibrium to_read color_me_skeptical https://pinboard.in/ https://pinboard.in/u:cshalizi/b:302abad9e4e5/ Lee , Song : Stable limit theorems for empirical processes under conditional neighborhood dependence 2019-05-25T03:01:30+00:00 https://projecteuclid.org/euclid.bj/1551862848 cshalizi to_read empirical_processes random_fields stochastic_processes central_limit_theorem in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f93b70f7625b/ Extremes in Random Fields | Wiley Series in Probability and Statistics 2019-01-07T17:50:30+00:00 https://onlinelibrary.wiley.com/doi/book/10.1002/9781118720608 cshalizi books:noted downloaded random_fields stochastic_processes extreme_values statistics spatial_statistics in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:e3b27f839d2c/ [1808.04739] Simulating Markov random fields with a conclique-based Gibbs sampler 2018-12-01T13:37:31+00:00 https://arxiv.org/abs/1808.04739 cshalizi random_fields simulation stochastic_processes spatial_statistics network_data_analysis markov_models statistics computational_statistics to_teach:data_over_space_and_time have_read in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:71d8eed500a5/ [math/0506080] Two new Markov order estimators 2018-09-23T22:17:23+00:00 https://arxiv.org/abs/math/0506080 cshalizi in_NB markov_models statistical_inference_for_stochastic_processes model_selection recurrence_times entropy_estimation information_theory stochastic_processes have_read have_talked_about random_fields https://pinboard.in/ https://pinboard.in/u:cshalizi/b:9585ed556542/ Thomas-Agnan : Spline Functions and Stochastic Filtering 2016-04-16T15:13:50+00:00 http://projecteuclid.org/euclid.aos/1176348259 cshalizi to:NB splines prediction filtering statistics hilbert_space fourier_analysis random_fields have_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f733830bbdcd/ Information flow on graphs | The Information Structuralist 2015-05-20T16:00:24+00:00 https://infostructuralist.wordpress.com/2014/05/03/information-flow-on-graphs/ cshalizi information_theory cellular_automata stochastic_processes mixing random_fields markov_models to:blog https://pinboard.in/ https://pinboard.in/u:cshalizi/b:270fa18b9ed2/ Learning Heterogeneous Hidden Markov Random Fields | AISTATS 2014 | JMLR W&CP 2014-04-20T17:46:32+00:00 http://jmlr.org/proceedings/papers/v33/liu14.html cshalizi to:NB markov_models random_fields statistics computational_statistics em_algorithm https://pinboard.in/ https://pinboard.in/u:cshalizi/b:082c1582939f/ Conditional Random Fields via Univariate Exponential Families 2014-01-04T03:34:39+00:00 http://papers.nips.cc/paper/5154-conditional-random-fields-via-univariate-exponential-families cshalizi random_fields exponential_families graphical_models statistics in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:2dedac961c9a/ [1104.3074] Consistency of the mean and the principal components of spatially distributed functional data 2013-12-14T16:35:51+00:00 http://arxiv.org/abs/1104.3074 cshalizi to:NB functional_data_analysis spatial_statistics random_fields statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:e1498546eaf2/ [1310.2646] Localized Iterative Methods for Interpolation in Graph Structured Data 2013-10-17T13:08:52+00:00 http://arxiv.org/abs/1310.2646 cshalizi smoothing random_fields network_data_analysis re:small-area_estimation_by_smoothing in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:914379738cc4/ [1308.6342] Efficient Learning of Practical Markov Random Fields with Exact Inference 2013-10-12T00:13:31+00:00 http://arxiv.org/abs/1308.6342 cshalizi to:NB markov_models random_fields graphical_models computational_statistics statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:bfee5037fd1b/ [1309.6702] Statistical paleoclimate reconstructions via Markov random fields 2013-09-27T16:45:27+00:00 http://arxiv.org/abs/1309.6702 cshalizi to:NB climatology variance_estimation random_fields sparsity statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:77aa4d790174/ Spatio-temporal random fields: compressible representation and distributed estimation - Springer 2013-08-17T19:02:53+00:00 http://link.springer.com/article/10.1007/s10994-013-5399-7 cshalizi random_fields graphical_models computational_statistics spatio-temporal_statistics to_read in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:67cf1987c635/ [1109.2694] Kernel density estimation for stationary random fields 2013-07-29T19:57:46+00:00 http://arxiv.org/abs/1109.2694 cshalizi to:NB density_estimation statistics random_fields mixing https://pinboard.in/ https://pinboard.in/u:cshalizi/b:5d228c8d75c8/ [1307.3617] MCMC Learning 2013-07-16T16:53:40+00:00 http://arxiv.org/abs/1307.3617 cshalizi to:NB learning_theory markov_models random_fields mossel.elchanan https://pinboard.in/ https://pinboard.in/u:cshalizi/b:d9fe83eeda3c/ [1307.1379] Multivariate Gaussian Random Fields Using Systems of Stochastic Partial Differential Equations 2013-07-08T16:34:41+00:00 http://arxiv.org/abs/1307.1379 cshalizi computational_statistics random_fields stochastic_differential_equations stochastic_processes spatial_statistics statistics in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:e9d946472b64/ [1307.1565] Concentration inequalities for smooth random fields 2013-07-08T16:32:27+00:00 http://arxiv.org/abs/1307.1565 cshalizi random_fields empirical_processes concentration_of_measure stochastic_processes re:almost_none in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:145934415469/ [1306.6205] Extrapolation of Stationary Random Fields 2013-06-27T15:27:07+00:00 http://arxiv.org/abs/1306.6205 cshalizi spatial_statistics prediction random_fields statistics to_teach:data_over_space_and_time in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:277890bb07ee/ Forbes , Charras-Garrido , Azizi , Doyle , Abrial : Spatial risk mapping for rare disease with hidden Markov fields and variational EM 2013-06-27T15:09:18+00:00 http://projecteuclid.org/DPubS?service=UI&version=1.0&verb=Display&handle=euclid.aoas/1372338484 cshalizi spatial_statistics estimation epidemiology random_fields markov_models statistics have_read in_NB re:small-area_estimation_by_smoothing https://pinboard.in/ https://pinboard.in/u:cshalizi/b:3a64f128c707/ [1306.2295] Markov random fields factorization with context-specific independences 2013-06-12T20:00:42+00:00 http://arxiv.org/abs/1306.2295 cshalizi to:NB markov_models random_fields graphical_models probability https://pinboard.in/ https://pinboard.in/u:cshalizi/b:b020f03d8c26/ [1302.5616] Large Deviations for Nonlocal Stochastic Neural Fields 2013-03-27T14:10:59+00:00 http://arxiv.org/abs/1302.5616 cshalizi random_fields neural_networks stochastic_differential_equations large_deviations in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:8572f1a4cc5e/ Lévy-based Modelling in Brain Imaging - JÓNSDÓTTIR - 2013 - Scandinavian Journal of Statistics - Wiley Online Library 2013-02-23T17:43:07+00:00 http://onlinelibrary.wiley.com/doi/10.1002/sjos.12000/abstract cshalizi to:NB neuroscience fmri random_fields spatial_statistics levy_processes cumulants https://pinboard.in/ https://pinboard.in/u:cshalizi/b:5864833c3e57/ Central Limit Theorems for Weakly Dependent Random Fields - Springer 2013-02-12T01:43:44+00:00 http://link.springer.com/chapter/10.1007%2F978-3-642-33305-7_10 cshalizi to:NB central_limit_theorem stochastic_processes mixing random_fields https://pinboard.in/ https://pinboard.in/u:cshalizi/b:d234ea141b38/ Kernel spatial density estimation in infinite dimension space - Springer 2013-01-07T04:08:23+00:00 http://link.springer.com/article/10.1007/s00184-011-0374-4 cshalizi to:NB density_estimation statistics random_fields https://pinboard.in/ https://pinboard.in/u:cshalizi/b:34626e06fe83/ An Introduction to Conditional Random Fields 2012-08-23T17:57:40+00:00 http://www.nowpublishers.com/product.aspx?product=MAL&doi=2200000013 cshalizi to:NB random_fields graphical_models machine_learning https://pinboard.in/ https://pinboard.in/u:cshalizi/b:e08017fb2e76/ [1206.2303] Population oscillations in spatial stochastic Lotka-Volterra models: A field-theoretic perturbational analysis 2012-06-23T15:15:04+00:00 http://arxiv.org/abs/1206.2303 cshalizi to:NB lotka-volterra ecology field_theory stochastic_processes random_fields https://pinboard.in/ https://pinboard.in/u:cshalizi/b:5add7359e10c/ [1206.3985] Computing the Cramer-Rao bound of Markov random field parameters: Application to the Ising and the Potts models 2012-06-19T14:33:48+00:00 http://arxiv.org/abs/1206.3985 cshalizi spatial_statistics random_fields markov_models fisher_information exponential_families statistics in_NB cramer-rao_inequality https://pinboard.in/ https://pinboard.in/u:cshalizi/b:8d34c4c6630e/ [1206.2398] LICORS: Light Cone Reconstruction of States for Non-parametric Forecasting of Spatio-Temporal Systems 2012-06-17T22:57:27+00:00 http://arxiv.org/abs/1206.2398 cshalizi self-promotion to:blog prediction statistics random_fields spatial_statistics dynamical_systems https://pinboard.in/ https://pinboard.in/u:cshalizi/b:c64ad2eb72f9/