Pinboard (cshalizi) https://pinboard.in/u:cshalizi/public/ recent bookmarks from cshalizi [2510.06136] Geometric Model Selection for Latent Space Network Models: Hypothesis Testing via Multidimensional Scaling and Resampling Techniques 2026-01-30T12:09:41+00:00 https://arxiv.org/abs/2510.06136 cshalizi to:NB network_data_analysis multidimensional_scaling re:hyperbolic_networks inference_to_latent_objects https://pinboard.in/ https://pinboard.in/u:cshalizi/b:9dfccc0379ec/ Variational Autoencoders and Nonlinear ICA: A Unifying Framework 2025-08-05T13:22:52+00:00 https://proceedings.mlr.press/v108/khemakhem20a.html cshalizi independent_components_analysis factor_analysis inference_to_latent_objects in_NB have_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:6e753df8293c/ [2506.01622] General agents need world models 2025-07-28T14:13:15+00:00 https://arxiv.org/abs/2506.01622 cshalizi to:NB artificial_intelligence control_theory_and_control_engineering inference_to_latent_objects internal_model_principle https://pinboard.in/ https://pinboard.in/u:cshalizi/b:e8910d3979af/ [2505.12540] Harnessing the Universal Geometry of Embeddings 2025-06-15T16:07:40+00:00 https://arxiv.org/abs/2505.12540 cshalizi to:NB neural_networks inference_to_latent_objects text_mining large_language_models_(so_called) https://pinboard.in/ https://pinboard.in/u:cshalizi/b:d6d9dd7f0540/ [2503.16865] Nonparametric Factor Analysis and Beyond 2025-04-28T01:20:54+00:00 https://arxiv.org/abs/2503.16865 cshalizi to:NB factor_analysis inference_to_latent_objects to_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:1a1eb5a9926a/ A Simple Latent Variable Model for Graph Learning and Inference | OpenReview 2025-03-08T14:04:47+00:00 https://openreview.net/forum?id=S9jem2KZVr cshalizi to:NB stochastic_block_models graphons re:smoothing_adjacency_matrices jaeger.manfred schulte.oliver to_read inference_to_latent_objects relational_learning https://pinboard.in/ https://pinboard.in/u:cshalizi/b:e826d2031bb8/ [2301.07473] Discrete Latent Structure in Neural Networks 2024-09-19T20:05:09+00:00 https://arxiv.org/abs/2301.07473 cshalizi neural_networks inference_to_latent_objects in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:6c808337d1a2/ Nonlinear Factor Analysis as a Statistical Method 2024-03-28T01:46:43+00:00 https://projecteuclid.org/journals/statistical-science/volume-16/issue-3/Nonlinear-Factor-Analysis-as-a-Statistical-Method/10.1214/ss/1009213729.full cshalizi in_NB factor_analysis inference_to_latent_objects re:generalized_additive_factor_models https://pinboard.in/ https://pinboard.in/u:cshalizi/b:2f618496c2eb/ [2401.01404v2] Scalable network reconstruction in subquadratic time 2024-01-11T01:12:15+00:00 https://arxiv.org/abs/2401.01404v2 cshalizi to:NB network_data_analysis inference_to_latent_objects piexoto.tiago_p. computational_statistics via:rvenkat https://pinboard.in/ https://pinboard.in/u:cshalizi/b:8414c5373c7d/ Does the d (disease) factor really exist? » Eiko Fried 2023-05-15T15:27:27+00:00 https://eiko-fried.com/does-the-d-disease-factor-really-exist/ cshalizi inference_to_latent_objects have_read track_down_references utter_stupidity factor_analysis i_have_lived_and_fought_in_vain https://pinboard.in/ https://pinboard.in/u:cshalizi/b:9d07ec8ad858/ [2212.02987] Generative probabilistic matrix model of data with different low-dimensional linear latent structures 2023-04-17T18:18:12+00:00 https://arxiv.org/abs/2212.02987 cshalizi factor_analysis high-dimensional_statistics inference_to_latent_objects nemenman.ilya re:g_paper in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:ebfab92bcab3/ [2111.04641] Statistical properties of large data sets with linear latent features 2023-04-17T18:14:32+00:00 https://arxiv.org/abs/2111.04641 cshalizi factor_analysis high-dimensional_statistics inference_to_latent_objects nemenman.ilya re:g_paper have_read in_NB random_matrices https://pinboard.in/ https://pinboard.in/u:cshalizi/b:b9e77dccb3c3/ [2212.08765] Latent Variable Representation for Reinforcement Learning 2023-03-24T18:50:29+00:00 https://arxiv.org/abs/2212.08765 cshalizi to:NB reinforcement_learning inference_to_latent_objects https://pinboard.in/ https://pinboard.in/u:cshalizi/b:05f33ce709d1/ Network Inference Using the Hub Model and Variants: Journal of the American Statistical Association: Vol 0, No ja 2023-03-18T13:57:06+00:00 https://www.tandfonline.com/doi/abs/10.1080/01621459.2023.2183133 cshalizi inference_to_latent_objects functional_connectivity network_data_analysis time_series to_read bickel.peter in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:fdee119e04f3/ Large Language Model: world models or surface statistics? 2023-01-23T04:11:33+00:00 https://thegradient.pub/othello/ cshalizi have_read neural_networks inference_to_latent_objects large_language_models_(so_called) in_NB to_teach:statistics_and_generative_ai https://pinboard.in/ https://pinboard.in/u:cshalizi/b:52c9ed05b79c/ [2210.13382] Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task 2023-01-23T03:57:06+00:00 https://arxiv.org/abs/2210.13382 cshalizi to_read inference_to_latent_objects neural_networks natural_language_processing large_language_models_(so_called) in_NB to_teach:statistics_and_generative_ai https://pinboard.in/ https://pinboard.in/u:cshalizi/b:26d3eeadeef9/ Measuring the non-existent: validity before measurement - PhilSci-Archive 2023-01-19T04:27:40+00:00 http://philsci-archive.pitt.edu/21626/ cshalizi to:NB measurement philosophy_of_science inference_to_latent_objects https://pinboard.in/ https://pinboard.in/u:cshalizi/b:b7a1fba2bbe0/ [2210.11021] Independence Testing-Based Approach to Causal Discovery under Measurement Error and Linear Non-Gaussian Models 2022-12-09T20:02:54+00:00 https://arxiv.org/abs/2210.11021 cshalizi to:NB causal_inference inference_to_latent_objects spirtes.peter zhang.kun to_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:b389406b2d4e/ [2210.07491] Latent process models for functional network data 2022-12-09T20:01:58+00:00 https://arxiv.org/abs/2210.07491 cshalizi to:NB network_data_analysis statistics inference_to_latent_objects functional_data_analysis levina.liza to_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:df335b19ec43/ Automated discovery of fundamental variables hidden in experimental data | Nature Computational Science 2022-08-27T19:42:49+00:00 https://www.nature.com/articles/s43588-022-00281-6 cshalizi to:NB inference_to_latent_objects equations_of_motion_from_a_time_series lipson.hod color_me_skeptical to_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:756af7ada2d8/ Probabilistic Numerics 2022-06-30T17:53:01+00:00 https://www.cambridge.org/core/books/probabilistic-numerics/0EBFF0B15E2481099F6EED1F62EE1ABE#fndtn-information cshalizi to:NB books:noted numerical_methods computational_statistics inference_to_latent_objects color_me_skeptical downloaded https://pinboard.in/ https://pinboard.in/u:cshalizi/b:8b03d12ff5c2/ Dynamic Deconvolution and Identification of Independent Autoregressive Sources - Gourieroux - - Journal of Time Series Analysis - Wiley Online Library 2022-06-21T14:04:12+00:00 https://onlinelibrary.wiley.com/doi/abs/10.1111/jtsa.12659?campaign=wolacceptedarticle cshalizi to:NB time_series factor_analysis independent_component inference_to_latent_objects https://pinboard.in/ https://pinboard.in/u:cshalizi/b:2e2ef805a54e/ The Shortest Path to Network Geometry 2022-01-10T20:04:38+00:00 https://doi.org/10.1017/9781108865791 cshalizi to:NB network_data_analysis hyperbolic_geometry geometry inference_to_latent_objects re:hyperbolic_networks to_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:b1527a8324c7/ [2112.00183] Descriptive vs. inferential community detection: pitfalls, myths and half-truths 2021-12-07T14:37:42+00:00 https://arxiv.org/abs/2112.00183 cshalizi to:NB to_read community_discovery network_data_analysis inference_to_latent_objects peixoto.tiago to_teach:baby-nets https://pinboard.in/ https://pinboard.in/u:cshalizi/b:17d3ef93eb8c/ [2110.03973] Many Proxy Controls 2021-12-05T17:06:35+00:00 https://arxiv.org/abs/2110.03973 cshalizi to:NB causal_inference inference_to_latent_objects to_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:6a3b1e623127/ Community detection with nodal information: likelihood and its variational approximation - Weng - - Stat - Wiley Online Library 2021-10-18T13:55:08+00:00 https://onlinelibrary.wiley.com/doi/abs/10.1002/sta4.428 cshalizi to:NB community_discovery network_data_analysis inference_to_latent_objects https://pinboard.in/ https://pinboard.in/u:cshalizi/b:14a346f001cd/ [2009.04096] A Joint MLE Approach to Large-Scale Structured Latent Attribute Analysis 2021-07-12T15:32:33+00:00 https://arxiv.org/abs/2009.04096 cshalizi to:NB mixture_models clustering inference_to_latent_objects likelihood psychometrics statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:be792de6fa63/ Improving the Measurement of Shared Cultural Schemas with Correlational Class Analysis: Theory and Method | Sociological Science 2021-06-27T18:49:19+00:00 https://sociologicalscience.com/articles-v4-15-353/ cshalizi to:NB surveys dimension_reduction inference_to_latent_objects social_measurement sociology via:gabriel_rossman statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:ef8371b87faf/ [2105.14093] Variational Inference for Latent Space Models for Dynamic Networks 2021-06-01T17:32:02+00:00 https://arxiv.org/abs/2105.14093 cshalizi to:NB networks_in_and_over_time inference_to_latent_objects computational_statistics network_data_analysis statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:6fcea7ea261d/ Statistical Applications in Educational Measurement | Annual Review of Statistics and Its Application 2021-06-01T13:40:59+00:00 https://www.annualreviews.org/doi/abs/10.1146/annurev-statistics-042720-104044 cshalizi to:NB education mental_testing social_measurement psychometrics inference_to_latent_objects statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f3ccd2e186a7/ [2006.15899] A statistical test to reject the structural interpretation of a latent factor model 2021-03-15T06:18:01+00:00 https://arxiv.org/abs/2006.15899 cshalizi to:NB factor_analysis causal_inference to_read re:g_paper inference_to_latent_objects https://pinboard.in/ https://pinboard.in/u:cshalizi/b:9f011cbbf1e1/ [2004.03569] Latent Network Structure Learning from High Dimensional Multivariate Point Processes 2021-01-25T16:10:53+00:00 https://arxiv.org/abs/2004.03569 cshalizi to:NB network_data_analysis point_processes inference_to_latent_objects https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f46899af7cc2/ Thesis Commons | Interpreting psychometric models 2021-01-10T16:16:22+00:00 https://thesiscommons.org/x6a7s/ cshalizi to:NB psychometrics statistics inference_to_latent_objects re:g_paper https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f886bf9b99bf/ [2101.02332] Identification of Latent Variables From Graphical Model Residuals 2021-01-08T03:39:39+00:00 https://arxiv.org/abs/2101.02332 cshalizi to:NB causal_discovery graphical_models inference_to_latent_objects statistics to_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:653363dd410a/ [2002.02250] Uncovering differential equations from data with hidden variables 2020-12-26T17:46:56+00:00 https://arxiv.org/abs/2002.02250 cshalizi equations_of_motion_from_a_time_series sparsity linear_regression dynamical_systems inference_to_latent_objects in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:3ba9d3e1c481/ Athreya , Tang , Park , Priebe : On Estimation and Inference in Latent Structure Random Graphs 2020-12-21T14:09:56+00:00 https://projecteuclid.org/euclid.ss/1608541219 cshalizi to:NB network_data_analysis statistics inference_to_latent_objects re:hyperbolic_networks https://pinboard.in/ https://pinboard.in/u:cshalizi/b:308a3adb0fa2/ [2012.05849] The Promises of Parallel Outcomes 2020-12-12T18:12:32+00:00 https://arxiv.org/abs/2012.05849 cshalizi to:NB causal_inference inference_to_latent_objects identifiability https://pinboard.in/ https://pinboard.in/u:cshalizi/b:d0a7af842a4d/ [1807.10399] Applications of Common Entropy for Causal Inference 2020-12-12T03:26:38+00:00 https://arxiv.org/abs/1807.10399 cshalizi to:NB causal_discovery information_theory inference_to_latent_objects or_rather_inference_to_the_absence_of_latent_objects https://pinboard.in/ https://pinboard.in/u:cshalizi/b:4020b84b3fad/ [2012.02677] Reconstructing networks 2020-12-07T15:11:07+00:00 https://arxiv.org/abs/2012.02677 cshalizi to:NB network_data_analysis inference_to_latent_objects https://pinboard.in/ https://pinboard.in/u:cshalizi/b:101295b40793/ Estimating Number of Factors by Adjusted Eigenvalues Thresholding: Journal of the American Statistical Association: Vol 0, No 0 2020-11-28T03:34:08+00:00 https://www.tandfonline.com/doi/full/10.1080/01621459.2020.1825448 cshalizi to:NB factor_analysis inference_to_latent_objects statistics model_selection re:g_paper https://pinboard.in/ https://pinboard.in/u:cshalizi/b:49f7ce4309d8/ [2008.03971] A Note on Likelihood Ratio Tests for Models with Latent Variables 2020-11-25T14:35:28+00:00 https://arxiv.org/abs/2008.03971 cshalizi to:NB factor_analysis mixture_models inference_to_latent_objects hypothesis_testing likelihood statistics re:HEAS https://pinboard.in/ https://pinboard.in/u:cshalizi/b:4d387d3303d2/ [2011.09465] Detecting Hierarchical Changes in Latent Variable Models 2020-11-23T17:36:44+00:00 https://arxiv.org/abs/2011.09465 cshalizi to:NB inference_to_latent_objects statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:7560ce908daa/ Kneip , Liebl : On the optimal reconstruction of partially observed functional data 2020-11-18T22:43:06+00:00 https://projecteuclid.org/euclid.aos/1594972835 cshalizi to:NB inverse_problems inference_to_latent_objects regression functional_data_analysis statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:98c00fa6e59e/ [1910.04333] Efficient Estimation for Random Dot Product Graphs via a One-step Procedure 2020-11-16T16:26:31+00:00 https://arxiv.org/abs/1910.04333 cshalizi to:NB network_data_analysis statistics inference_to_latent_objects continuous_latent_space_network_models https://pinboard.in/ https://pinboard.in/u:cshalizi/b:a9bc9430bec9/ Barigozzi , Cho : Consistent estimation of high-dimensional factor models when the factor number is over-estimated 2020-11-16T16:23:26+00:00 https://projecteuclid.org/euclid.ejs/1597197614 cshalizi time_series factor_analysis high-dimensional_statistics inference_to_latent_objects statistics principal_components in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:6a8174061a91/ Semidefinite Tests for Latent Causal Structures - IEEE Journals & Magazine 2020-11-16T16:04:42+00:00 https://ieeexplore.ieee.org/document/8804234 cshalizi to:NB causal_discovery graphical_models statistics hypothesis_testing inference_to_latent_objects https://pinboard.in/ https://pinboard.in/u:cshalizi/b:9caefd16483a/ PsyArXiv Preprints | Implicit realism impedes progress in psychology: Comment on Fried (2020) 2020-09-24T19:05:11+00:00 https://psyarxiv.com/xj5uq cshalizi to:NB social_science_methodology inference_to_latent_objects factor_analysis re:g_paper yarkoni.tal https://pinboard.in/ https://pinboard.in/u:cshalizi/b:e74ca65db7ad/ [2003.08505] A Metric Learning Reality Check 2020-08-08T15:01:06+00:00 https://arxiv.org/abs/2003.08505 cshalizi to:NB inference_to_latent_objects metric_learning neural_networks your_favorite_deep_neural_network_sucks via:? https://pinboard.in/ https://pinboard.in/u:cshalizi/b:0d7f83fb7fc4/ The Ongoing Accomplishment of the Big Five – Carcinisation 2020-07-16T16:04:33+00:00 https://carcinisation.com/2020/07/04/the-ongoing-accomplishment-of-the-big-five/ cshalizi personality_tests inference_to_latent_objects psychology https://pinboard.in/ https://pinboard.in/u:cshalizi/b:b19b300cd00a/ Asymptotic Model Selection for Directed Networks with Hidden Variables | SpringerLink 2020-05-16T18:08:16+00:00 https://link.springer.com/chapter/10.1007/978-94-011-5014-9_16 cshalizi to:NB have_read to_reread information_criteria information_geometry statistics likelihood graphical_models inference_to_latent_objects re:HEAS https://pinboard.in/ https://pinboard.in/u:cshalizi/b:2a65e9c78eb7/ [2005.02511] Bias-Variance Tradeoffs in Joint Spectral Embeddings 2020-05-13T17:27:04+00:00 https://arxiv.org/abs/2005.02511 cshalizi to:NB graph_embedding network_data_analysis inference_to_latent_objects statistics to_read continuous_latent_space_network_models https://pinboard.in/ https://pinboard.in/u:cshalizi/b:dd964fd45045/ [1902.10288] Clustering, factor discovery and optimal transport 2020-01-31T00:20:49+00:00 https://arxiv.org/abs/1902.10288 cshalizi to:NB clustering factor_analysis inference_to_latent_objects statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:9c27e8511952/ Generalized Network Psychometrics: Combining Network and Latent Variable Models | SpringerLink 2020-01-26T16:32:39+00:00 https://link.springer.com/article/10.1007/s11336-017-9557-x cshalizi to:NB factor_analysis graphical_models borsboom.denny psychometrics inference_to_latent_objects statistics re:g_paper re:major_depression_qu'est-ce_que_c'est have_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:e10094c749c8/ Network Effects in Blau Space: Imputing Social Context from Survey Data - Miller McPherson, Jeffrey A. Smith, 2019 2020-01-09T22:04:36+00:00 https://journals.sagepub.com/doi/full/10.1177/2378023119868591 cshalizi to:NB to_read homophily sociology social_influence re:homophily_and_confounding missing_data inference_to_latent_objects color_me_skeptical https://pinboard.in/ https://pinboard.in/u:cshalizi/b:07d3b393c731/ Unsupervised identification of the internal states that shape natural behavior | Nature Neuroscience 2019-11-26T15:27:40+00:00 https://www.nature.com/articles/s41593-019-0533-x cshalizi to:NB neuroscience state-space_models time_series psychology inference_to_latent_objects statistics to_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:8bb625685c95/ The relationship between external variables and common factors | SpringerLink 2019-11-26T08:45:22+00:00 https://link.springer.com/article/10.1007/BF02293788 cshalizi have_read factor_analysis inference_to_latent_objects psychometrics statistics re:g_paper in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:65bedbdaa9d9/ Factor indeterminacy in the 1930's and the 1970's some interesting parallels | SpringerLink 2019-11-26T08:39:01+00:00 https://link.springer.com/article/10.1007%2FBF02293967 cshalizi psychometrics factor_analysis inference_to_latent_objects have_read a_long_time_ago re:g_paper in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:0068a61c1866/ [1910.14238] Learning Disentangled Representations for Recommendation 2019-11-11T20:04:41+00:00 https://arxiv.org/abs/1910.14238 cshalizi to:NB information_bottleneck inference_to_latent_objects recommender_systems statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f101276df0d6/ Modeling Uncertainty in Latent Class Membership: A Case Study in Criminology on JSTOR 2019-11-09T02:31:30+00:00 https://www.jstor.org/stable/2669989?seq=1#metadata_info_tab_contents cshalizi to:NB crime time_series mixture_models kith_and_kin roeder.kathryn statistics inference_to_latent_objects have_skimmed https://pinboard.in/ https://pinboard.in/u:cshalizi/b:408d7df96513/ [1910.10174] Leveraging directed causal discovery to detect latent common causes 2019-10-24T14:35:34+00:00 https://arxiv.org/abs/1910.10174 cshalizi to:NB causal_discovery inference_to_latent_objects statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:56d5bd027c12/ [1910.08778] Measurement Dependence Inducing Latent Causal Models 2019-10-22T13:34:25+00:00 https://arxiv.org/abs/1910.08778 cshalizi to:NB inference_to_latent_objects causal_discovery statistics to_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:9b13cb38f84e/ [1910.06985] How a minimal learning agent can infer the existence of unobserved variables in a complex environment 2019-10-22T03:32:34+00:00 https://arxiv.org/abs/1910.06985 cshalizi to:NB artificial_intelligence inference_to_latent_objects color_me_skeptical https://pinboard.in/ https://pinboard.in/u:cshalizi/b:93ebe7a6b216/ [1910.00423] Limit theorems for out-of-sample extensions of the adjacency and Laplacian spectral embeddings 2019-10-02T15:55:30+00:00 https://arxiv.org/abs/1910.00423 cshalizi to:NB graph_embedding inference_to_latent_objects statistics network_data_analysis re:hyperbolic_networks https://pinboard.in/ https://pinboard.in/u:cshalizi/b:8d0c8b7f3c3a/ [1910.00163] Specializing Word Embeddings (for Parsing) by Information Bottleneck 2019-10-02T15:53:00+00:00 https://arxiv.org/abs/1910.00163 cshalizi to:NB information_bottleneck text_mining inference_to_latent_objects statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:55644087a65d/ [1909.11822] DisCo: Physics-Based Unsupervised Discovery of Coherent Structures in Spatiotemporal Systems 2019-10-01T15:03:03+00:00 https://arxiv.org/abs/1909.11822 cshalizi to:NB to_read kith_and_kin crutchfield.james_p. spatio-temporal_statistics inference_to_latent_objects predictive_state_representations statistics computational_statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:d5afd657b733/ [1909.06841] Latent Distance Estimation for Random Geometric Graphs 2019-09-25T04:04:00+00:00 https://arxiv.org/abs/1909.06841 cshalizi to:NB network_data_analysis re:hyperbolic_networks statistics inference_to_latent_objects to_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:45528bc09e72/ [1909.05229] Goodness-of-fit tests on manifolds 2019-09-15T17:27:33+00:00 https://arxiv.org/abs/1909.05229 cshalizi to:NB statistics_on_manifolds goodness-of-fit statistics inference_to_latent_objects manifold_learning https://pinboard.in/ https://pinboard.in/u:cshalizi/b:d3482b75f147/ [1909.03586] Curve Fitting from Probabilistic Emissions and Applications to Dynamic Item Response Theory 2019-09-15T14:25:29+00:00 https://arxiv.org/abs/1909.03586 cshalizi to:NB inference_to_latent_objects graphical_models statistics psychometrics non-stationarity https://pinboard.in/ https://pinboard.in/u:cshalizi/b:5b52b9085c6c/ [1908.08941] Data-driven modeling of strongly nonlinear chaotic systems with non-Gaussian statistics 2019-08-27T15:50:58+00:00 https://arxiv.org/abs/1908.08941 cshalizi to:NB heavy_tails stochastic_differential_equations inference_to_latent_objects dynamical_systems time_series statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:6afeb430746c/ [1811.06407] Neural Predictive Belief Representations 2019-08-20T14:25:50+00:00 https://arxiv.org/abs/1811.06407 cshalizi prediction predictive_representations inference_to_latent_objects neural_networks to_read uncertainty_for_neural_networks in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:1eb85f0036b8/