{"url":"/task/variable-selection","name":"Variable Selection","slug":"variable-selection","description_markdown":null,"categories":[{"name":"Methodology","url":"/area/methodology"}],"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","slug_source":"derived"},"counts":{"papers_tagged":566,"papers_with_code":145,"benchmarks":0,"benchmark_tables_in_archive":0,"benchmark_tables_shown":0,"benchmark_tables_withheld_as_spam":0,"benchmark_definition":"a leaderboard table with at least one row; benchmark_tables_shown also counts the zero-row tables; benchmark_tables_in_archive adds the tables withheld as spam","datasets":0,"subtasks":0,"parent_tasks":0},"benchmarks":[],"datasets":[],"subtasks":[],"parent_tasks":[],"papers":{"order":"repositories listed in the archive (desc), then date (desc); the archive holds no stars","population":"papers tagged with this task that list at least one repository in the archive","shown":30,"of":145,"tagged_in_all":566,"items":[{"url":"/paper/exact-combinatorial-optimization-with-graph","title":"Exact Combinatorial Optimization with Graph Convolutional Neural Networks","date":"2019-06-04","arxiv_id":"1906.01629","repositories_listed":6,"syntology":{"n":2,"n_ran":0,"n_unverified":2,"n_pointer_only":1}},{"url":"/paper/deep-knockoffs","title":"Deep Knockoffs","date":"2018-11-16","arxiv_id":"1811.06687","repositories_listed":4,"syntology":null},{"url":"/paper/neural-interval-censored-cox-regression-with","title":"Neural interval-censored survival regression with feature selection","date":"2022-06-14","arxiv_id":"2206.06885","repositories_listed":3,"syntology":null},{"url":"/paper/trading-with-the-momentum-transformer-an","title":"Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture","date":"2021-12-16","arxiv_id":"2112.08534","repositories_listed":3,"syntology":null},{"url":"/paper/bart-bayesian-additive-regression-trees","title":"BART: Bayesian additive regression trees","date":"2008-06-19","arxiv_id":"0806.3286","repositories_listed":3,"syntology":{"n":1,"n_ran":1,"n_unverified":0,"n_pointer_only":0}},{"url":"/paper/stability-selection-via-variable","title":"Stability Selection via Variable Decorrelation","date":"2025-05-27","arxiv_id":"2505.20864","repositories_listed":2,"syntology":null},{"url":"/paper/on-the-selection-stability-of-stability","title":"On the Selection Stability of Stability Selection and Its Applications","date":"2024-11-14","arxiv_id":"2411.09097","repositories_listed":2,"syntology":null},{"url":"/paper/bayesian-variable-selection-in-a-million","title":"Bayesian Variable Selection in a Million Dimensions","date":"2022-08-02","arxiv_id":"2208.01180","repositories_listed":2,"syntology":null},{"url":"/paper/omicselector-automatic-feature-selection-and","title":"OmicSelector: automatic feature selection and deep learning modeling for omic experiments","date":"2022-06-02","arxiv_id":null,"repositories_listed":2,"syntology":null},{"url":"/paper/scalable-spike-and-slab","title":"Scalable Spike-and-Slab","date":"2022-04-04","arxiv_id":"2204.01668","repositories_listed":2,"syntology":{"n":19,"n_ran":7,"n_unverified":12,"n_pointer_only":19}},{"url":"/paper/flexible-variable-selection-in-the-presence","title":"Flexible variable selection in the presence of missing data","date":"2022-02-25","arxiv_id":"2202.12989","repositories_listed":2,"syntology":null},{"url":"/paper/abess-a-fast-best-subset-selection-library-in","title":"abess: A Fast Best Subset Selection Library in Python and R","date":"2021-10-19","arxiv_id":"2110.09697","repositories_listed":2,"syntology":null},{"url":"/paper/post-selection-inference-with-hsic-lasso","title":"Post-selection inference with HSIC-Lasso","date":"2020-10-29","arxiv_id":"2010.15659","repositories_listed":2,"syntology":null},{"url":"/paper/nonconvex-regularized-robust-regression-with","title":"Iteratively Reweighted $\\ell_1$-Penalized Robust Regression","date":"2019-07-09","arxiv_id":"1907.04027","repositories_listed":2,"syntology":null},{"url":"/paper/variable-selection-for-gaussian-processes-via","title":"Variable selection for Gaussian processes via sensitivity analysis of the posterior predictive distribution","date":"2017-12-21","arxiv_id":"1712.08048","repositories_listed":2,"syntology":null},{"url":"/paper/bolasso-model-consistent-lasso-estimation","title":"Bolasso: model consistent Lasso estimation through the bootstrap","date":"2008-04-08","arxiv_id":"0804.1302","repositories_listed":2,"syntology":null},{"url":"/paper/handling-bounded-response-in-high-dimensions","title":"Handling bounded response in high dimensions: a Horseshoe prior Bayesian Beta regression approach","date":"2025-05-28","arxiv_id":"2505.22211","repositories_listed":1,"syntology":null},{"url":"/paper/high-dimensional-bayesian-optimization-using-2","title":"High Dimensional Bayesian Optimization using Lasso Variable Selection","date":"2025-04-02","arxiv_id":"2504.01743","repositories_listed":1,"syntology":null},{"url":"/paper/bayesian-cox-model-with-graph-structured","title":"Bayesian Cox model with graph-structured variable selection priors for multi-omics biomarker identification","date":"2025-03-17","arxiv_id":"2503.13078","repositories_listed":1,"syntology":null},{"url":"/paper/causal-feature-learning-in-the-social","title":"Causal Feature Learning in the Social Sciences","date":"2025-03-17","arxiv_id":"2503.12784","repositories_listed":1,"syntology":null},{"url":"/paper/aircast-improving-air-pollution-forecasting","title":"AirCast: Improving Air Pollution Forecasting Through Multi-Variable Data Alignment","date":"2025-02-25","arxiv_id":"2502.17919","repositories_listed":1,"syntology":null},{"url":"/paper/proximal-iteration-for-nonlinear-adaptive","title":"Proximal Iteration for Nonlinear Adaptive Lasso","date":"2024-12-07","arxiv_id":"2412.05726","repositories_listed":1,"syntology":null},{"url":"/paper/ab-initio-nonparametric-variable-selection","title":"Ab Initio Nonparametric Variable Selection for Scalable Symbolic Regression with Large $p$","date":"2024-10-17","arxiv_id":"2410.13681","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_unverified":0,"n_pointer_only":3}},{"url":"/paper/comorbid-anxiety-symptoms-predict-lower-odds","title":"Comorbid anxiety predicts lower odds of depression improvement during smartphone-delivered psychotherapy","date":"2024-09-16","arxiv_id":"2409.11183","repositories_listed":1,"syntology":null},{"url":"/paper/vicatmix-variational-bayesian-clustering-and","title":"VICatMix: variational Bayesian clustering and variable selection for discrete biomedical data","date":"2024-06-23","arxiv_id":"2406.16227","repositories_listed":1,"syntology":null},{"url":"/paper/introducing-sgboost-a-practical-guide-and","title":"Sparse-Group Boosting with Balanced Selection Frequencies: A Simulation-Based Approach and R Implementation","date":"2024-05-31","arxiv_id":"2405.21037","repositories_listed":1,"syntology":null},{"url":"/paper/deeplink-t-deep-learning-inference-for-time","title":"DeepLINK-T: deep learning inference for time series data using knockoffs and LSTM","date":"2024-04-05","arxiv_id":"2404.04317","repositories_listed":1,"syntology":null},{"url":"/paper/predictive-analytics-of-varieties-of-potatoes","title":"Predictive Analytics of Varieties of Potatoes","date":"2024-04-04","arxiv_id":"2404.03701","repositories_listed":1,"syntology":null},{"url":"/paper/high-dimensional-forecasting-with-known","title":"High-dimensional forecasting with known knowns and known unknowns","date":"2024-01-26","arxiv_id":"2401.14582","repositories_listed":1,"syntology":null},{"url":"/paper/information-theoretic-state-variable","title":"Information-Theoretic State Variable Selection for Reinforcement Learning","date":"2024-01-21","arxiv_id":"2401.11512","repositories_listed":1,"syntology":null}],"syntology_records":4,"syntology_note":"a paper without a record is not a recorded non-run: it may lack an arXiv id or simply be absent from the graph layer"},"description_links":{"kept":0,"unwrapped_to_text":0,"bare_urls_linked":0,"relative_images_dropped":0,"rule":"internal links are kept only when the target slug exists in the catalog"},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per-sample execution status on synthesized fixtures ('ran N of M samples'); not a correctness claim and not a ranking signal.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"}},"not_shown":{"libraries":"the archive has no per-task library table","trend_sparklines":"the Trend column of the benchmarks table was a rendered image; it is not in the archive","social_and_latest_sorts":"stars and social signals are not in the archive"}}