{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/dimensionality-reduction/papers/14","list_of":"/task/dimensionality-reduction","task":"Dimensionality Reduction","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":14,"pages_in_order":34,"rows_per_page":100,"rows":[1301,1400],"of":3304,"counts":{"archive_papers_tagged":3304,"with_a_code_link":857,"where_syntology_ran_a_sample":100,"not_listed_spam_title":0,"listed":3304,"listed_where_code_ran":100,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":84,"every_run_a_failure_of_syntologys_instrument":16,"listed_with_a_run_with_no_instrument_failure":84,"listed_every_run_a_failure_of_syntologys_instrument":16,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/dimensionality-reduction","prev":"/task/dimensionality-reduction/papers/13","next":"/task/dimensionality-reduction/papers/15","papers":[{"url":null,"slug":"inference-for-regression-with-variables","title":"Inference for Regression with Variables Generated by AI or Machine Learning","date":"2024-02-23","arxiv_id":"2402.15585","repositories_listed":0,"syntology":null},{"url":null,"slug":"non-contact-acquisition-of-ppg-signal-using","title":"Non-Contact Acquisition of PPG Signal using Chest Movement-Modulated Radio Signals","date":"2024-02-22","arxiv_id":"2402.14565","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-two-stage-dual-path-framework-for-text","title":"A Two-Stage Dual-Path Framework for Text Tampering Detection and Recognition","date":"2024-02-21","arxiv_id":"2402.13545","repositories_listed":0,"syntology":null},{"url":null,"slug":"discovering-behavioral-modes-in-deep","title":"Discovering Behavioral Modes in Deep Reinforcement Learning Policies Using Trajectory Clustering in Latent Space","date":"2024-02-20","arxiv_id":"2402.12939","repositories_listed":0,"syntology":null},{"url":null,"slug":"training-artificial-neural-networks-by-1","title":"Training Artificial Neural Networks by Coordinate Search Algorithm","date":"2024-02-20","arxiv_id":"2402.12646","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-enhanced-teaching-learning-based","title":"An enhanced Teaching-Learning-Based Optimization (TLBO) with Grey Wolf Optimizer (GWO) for text feature selection and clustering","date":"2024-02-19","arxiv_id":"2402.11839","repositories_listed":0,"syntology":null},{"url":null,"slug":"neuro-mimetic-task-free-unsupervised-online","title":"Neuro-mimetic Task-free Unsupervised Online Learning with Continual Self-Organizing Maps","date":"2024-02-19","arxiv_id":"2402.12465","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluating-the-stability-of-deep-learning","title":"Evaluating the Stability of Deep Learning Latent Feature Spaces","date":"2024-02-17","arxiv_id":"2402.11404","repositories_listed":0,"syntology":null},{"url":null,"slug":"fast-data-driven-greedy-sensor-selection-for","title":"Fast Data-driven Greedy Sensor Selection for Ridge Regression","date":"2024-02-16","arxiv_id":"2402.10596","repositories_listed":0,"syntology":null},{"url":null,"slug":"combating-financial-crimes-with-unsupervised","title":"Combating Financial Crimes with Unsupervised Learning Techniques: Clustering and Dimensionality Reduction for Anti-Money Laundering","date":"2024-02-14","arxiv_id":"2403.00777","repositories_listed":0,"syntology":null},{"url":null,"slug":"sagman-stability-analysis-of-graph-neural","title":"SAGMAN: Stability Analysis of Graph Neural Networks on the Manifolds","date":"2024-02-13","arxiv_id":"2402.08653","repositories_listed":0,"syntology":null},{"url":null,"slug":"injecting-wiktionary-to-improve-token-level","title":"Injecting Wiktionary to improve token-level contextual representations using contrastive learning","date":"2024-02-12","arxiv_id":"2402.07817","repositories_listed":0,"syntology":null},{"url":null,"slug":"understanding-deep-learning-defenses-against","title":"Understanding Deep Learning defenses Against Adversarial Examples Through Visualizations for Dynamic Risk Assessment","date":"2024-02-12","arxiv_id":"2402.07496","repositories_listed":0,"syntology":null},{"url":null,"slug":"you-can-monitor-your-hydration-level-using","title":"You can monitor your hydration level using your smartphone camera","date":"2024-02-12","arxiv_id":"2402.07467","repositories_listed":0,"syntology":null},{"url":null,"slug":"simple-unified-analysis-of-johnson","title":"Simple, unified analysis of Johnson-Lindenstrauss with applications","date":"2024-02-10","arxiv_id":"2402.10232","repositories_listed":0,"syntology":null},{"url":null,"slug":"dimensionality-reduction-can-be-used-as-a","title":"Dimensionality reduction can be used as a surrogate model for high-dimensional forward uncertainty quantification","date":"2024-02-07","arxiv_id":"2402.04582","repositories_listed":0,"syntology":null},{"url":null,"slug":"multilinear-kernel-regression-and-imputation","title":"Multilinear Kernel Regression and Imputation via Manifold Learning","date":"2024-02-06","arxiv_id":"2402.03648","repositories_listed":0,"syntology":null},{"url":"/paper/pqmass-probabilistic-assessment-of-the","slug":"pqmass-probabilistic-assessment-of-the","title":"PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation","date":"2024-02-06","arxiv_id":"2402.04355","repositories_listed":0,"syntology":{"n":10,"n_ran":8,"n_constructed":0,"n_ran_checked":2,"n_instrument":6,"n_unverified":2,"n_honours":2,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 6 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/pqmass-probabilistic-assessment-of-the#ran","syntology_url":"https://syntology.ai/paper/2402.04355","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2402.04355"}},"official":null}},{"url":null,"slug":"on-minimum-trace-factor-analysis-an-old-song","title":"On Minimum Trace Factor Analysis - An Old Song Sung to a New Tune","date":"2024-02-04","arxiv_id":"2402.02459","repositories_listed":0,"syntology":null},{"url":null,"slug":"distributional-reduction-unifying","title":"Distributional Reduction: Unifying Dimensionality Reduction and Clustering with Gromov-Wasserstein","date":"2024-02-03","arxiv_id":"2402.02239","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-modal-representation-learning-for-cross","title":"Multi-modal Representation Learning for Cross-modal Prediction of Continuous Weather Patterns from Discrete Low-Dimensional Data","date":"2024-01-30","arxiv_id":"2401.16936","repositories_listed":0,"syntology":null},{"url":null,"slug":"run-to-run-control-with-bayesian-optimization","title":"Run-to-Run Control With Bayesian Optimization for Soft Landing of Short-Stroke Reluctance Actuators","date":"2024-01-24","arxiv_id":"2401.13606","repositories_listed":0,"syntology":null},{"url":null,"slug":"accelerating-hyperbolic-t-sne","title":"Accelerating hyperbolic t-SNE","date":"2024-01-23","arxiv_id":"2401.13708","repositories_listed":0,"syntology":null},{"url":null,"slug":"iterated-relevance-matrix-analysis-irma-for","title":"Iterated Relevance Matrix Analysis (IRMA) for the identification of class-discriminative subspaces","date":"2024-01-23","arxiv_id":"2401.12842","repositories_listed":0,"syntology":null},{"url":null,"slug":"full-dimensional-characterisation-of-time","title":"Full-dimensional characterisation of time-warped spike-time stimulus-response distribution geometries","date":"2024-01-22","arxiv_id":"2401.11784","repositories_listed":0,"syntology":null},{"url":null,"slug":"machine-learning-based-network-intrusion","title":"Machine learning-based network intrusion detection for big and imbalanced data using oversampling, stacking feature embedding and feature extraction","date":"2024-01-22","arxiv_id":"2401.12262","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-learning-assisted-inverse-modeling","title":"Transfer learning-assisted inverse modeling in nanophotonics based on mixture density networks","date":"2024-01-21","arxiv_id":"2401.12254","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-dimensionality-reduction-of-twin-in","title":"Automatic dimensionality reduction of Twin-in-the-Loop Observers","date":"2024-01-18","arxiv_id":"2401.10945","repositories_listed":0,"syntology":null},{"url":null,"slug":"comprehensive-ood-detection-improvements","title":"Comprehensive OOD Detection Improvements","date":"2024-01-18","arxiv_id":"2401.10176","repositories_listed":0,"syntology":null},{"url":null,"slug":"content-aware-tweet-location-inference-using","title":"Content-Aware Tweet Location Inference using Quadtree Spatial Partitioning and Jaccard-Cosine Word Embedding","date":"2024-01-16","arxiv_id":"2401.08506","repositories_listed":0,"syntology":null},{"url":null,"slug":"differentially-private-sliced-inverse-1","title":"Differentially Private Sliced Inverse Regression: Minimax Optimality and Algorithm","date":"2024-01-16","arxiv_id":"2401.08150","repositories_listed":0,"syntology":null},{"url":null,"slug":"mobile-contactless-palmprint-recognition-use","title":"Mobile Contactless Palmprint Recognition: Use of Multiscale, Multimodel Embeddings","date":"2024-01-16","arxiv_id":"2401.08111","repositories_listed":0,"syntology":null},{"url":null,"slug":"sparse-pca-with-false-discovery-rate","title":"Sparse PCA with False Discovery Rate Controlled Variable Selection","date":"2024-01-16","arxiv_id":"2401.08375","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-preserving-feature-partitioning-for","title":"Semantic-Preserving Feature Partitioning for Multi-View Ensemble Learning","date":"2024-01-11","arxiv_id":"2401.06251","repositories_listed":0,"syntology":null},{"url":null,"slug":"empirical-analysis-of-anomaly-detection-on","title":"Empirical Analysis of Anomaly Detection on Hyperspectral Imaging Using Dimension Reduction Methods","date":"2024-01-09","arxiv_id":"2401.04437","repositories_listed":0,"syntology":null},{"url":null,"slug":"dynamic-and-memory-efficient-shape-based","title":"Dynamic and Memory-efficient Shape Based Methodologies for User Type Identification in Smart Grid Applications","date":"2024-01-07","arxiv_id":"2401.03352","repositories_listed":0,"syntology":null},{"url":null,"slug":"nonlinear-functional-regression-by-functional","title":"Nonlinear functional regression by functional deep neural network with kernel embedding","date":"2024-01-05","arxiv_id":"2401.02890","repositories_listed":0,"syntology":null},{"url":null,"slug":"scalable-manifold-learning-by-uniform","title":"Scalable manifold learning by uniform landmark sampling and constrained locally linear embedding","date":"2024-01-02","arxiv_id":"2401.01100","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-novel-method-for-schizophrenia","title":"A Novel method for Schizophrenia classification using nonlinear features and neural networks","date":"2023-12-30","arxiv_id":"2402.14819","repositories_listed":0,"syntology":null},{"url":null,"slug":"analytic-understanding-decision-boundaries","title":"ANALYTiC: Understanding Decision Boundaries and Dimensionality Reduction in Machine Learning","date":"2023-12-29","arxiv_id":"2401.05418","repositories_listed":0,"syntology":null},{"url":null,"slug":"agnostically-learning-multi-index-models-with","title":"Agnostically Learning Multi-index Models with Queries","date":"2023-12-27","arxiv_id":"2312.16616","repositories_listed":0,"syntology":null},{"url":null,"slug":"comparative-analysis-of-radiomic-features-and","title":"Comparative Analysis of Radiomic Features and Gene Expression Profiles in Histopathology Data Using Graph Neural Networks","date":"2023-12-25","arxiv_id":"2312.15825","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-estimation-of-the-central-mean","title":"Efficient Estimation of the Central Mean Subspace via Smoothed Gradient Outer Products","date":"2023-12-24","arxiv_id":"2312.15469","repositories_listed":0,"syntology":null},{"url":null,"slug":"nowcasting-madagascar-s-real-gdp-using","title":"Nowcasting Madagascar's real GDP using machine learning algorithms","date":"2023-12-24","arxiv_id":"2401.10255","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-efficient-gwas-feature","title":"Deep Learning for Efficient GWAS Feature Selection","date":"2023-12-22","arxiv_id":"2312.15055","repositories_listed":0,"syntology":null},{"url":null,"slug":"augment-on-manifold-mixup-regularization-with","title":"Augment on Manifold: Mixup Regularization with UMAP","date":"2023-12-20","arxiv_id":"2312.13141","repositories_listed":0,"syntology":null},{"url":null,"slug":"convergence-visualizer-of-decentralized","title":"Convergence Visualizer of Decentralized Federated Distillation with Reduced Communication Costs","date":"2023-12-19","arxiv_id":"2312.11905","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-powerful-face-preprocessing-for-robust","title":"A Powerful Face Preprocessing For Robust Kinship Verification based Tensor Analyses","date":"2023-12-18","arxiv_id":"2312.11290","repositories_listed":0,"syntology":null},{"url":null,"slug":"language-assisted-3d-scene-understanding","title":"Language-Assisted 3D Scene Understanding","date":"2023-12-18","arxiv_id":"2312.11451","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-learning-for-fault-detection-of","title":"Unsupervised Learning for Fault Detection of HVAC Systems: An OPTICS -based Approach for Terminal Air Handling Units","date":"2023-12-18","arxiv_id":"2312.11405","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-new-method-color-ms-bsif-features-learning","title":"A new method color MS-BSIF Features learning for the robust kinship verification","date":"2023-12-16","arxiv_id":"2312.10482","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-umap-in-hybrid-models-of-entropy","title":"Exploring UMAP in hybrid models of entropy-based and representativeness sampling for active learning in biomedical segmentation","date":"2023-12-16","arxiv_id":"2312.10361","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-detection-of-zika-and-dengue-in","title":"Automated detection of Zika and dengue in Aedes aegypti using neural spiking analysis","date":"2023-12-14","arxiv_id":"2312.08654","repositories_listed":0,"syntology":null},{"url":null,"slug":"high-dimensional-bayesian-optimisation-with-1","title":"High-Dimensional Bayesian Optimisation with Large-Scale Constraints -- An Application to Aeroelastic Tailoring","date":"2023-12-14","arxiv_id":"2312.08891","repositories_listed":0,"syntology":null},{"url":null,"slug":"rdimkd-generic-distillation-paradigm-by","title":"RdimKD: Generic Distillation Paradigm by Dimensionality Reduction","date":"2023-12-14","arxiv_id":"2312.08700","repositories_listed":0,"syntology":null},{"url":"/paper/expand-and-quantize-unsupervised-semantic","slug":"expand-and-quantize-unsupervised-semantic","title":"Expand-and-Quantize: Unsupervised Semantic Segmentation Using High-Dimensional Space and Product Quantization","date":"2023-12-12","arxiv_id":"2312.07342","repositories_listed":0,"syntology":null},{"url":null,"slug":"federated-multilinear-principal-component","title":"Federated Multilinear Principal Component Analysis with Applications in Prognostics","date":"2023-12-11","arxiv_id":"2312.06050","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-quantitative-fusion-strategy-of-stock","title":"A quantitative fusion strategy of stock picking and timing based on Particle Swarm Optimized-Back Propagation Neural Network and Multivariate Gaussian-Hidden Markov Model","date":"2023-12-10","arxiv_id":"2312.05756","repositories_listed":0,"syntology":null},{"url":null,"slug":"economic-forecasts-using-many-noises","title":"Economic Forecasts Using Many Noises","date":"2023-12-09","arxiv_id":"2312.05593","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-robust-and-efficient-boundary-point","title":"A Robust and Efficient Boundary Point Detection Method by Measuring Local Direction Dispersion","date":"2023-12-07","arxiv_id":"2312.04065","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-masked-pruning-approach-for-dimensionality","title":"A Masked Pruning Approach for Dimensionality Reduction in Communication-Efficient Federated Learning Systems","date":"2023-12-06","arxiv_id":"2312.03889","repositories_listed":0,"syntology":null},{"url":null,"slug":"interpretability-illusions-in-the","title":"Interpretability Illusions in the Generalization of Simplified Models","date":"2023-12-06","arxiv_id":"2312.03656","repositories_listed":0,"syntology":null},{"url":null,"slug":"dimensionality-reduction-and-dynamical-mode","title":"Dimensionality Reduction and Dynamical Mode Recognition of Circular Arrays of Flame Oscillators Using Deep Neural Network","date":"2023-12-05","arxiv_id":"2312.02462","repositories_listed":0,"syntology":null},{"url":null,"slug":"geometric-data-driven-dimensionality","title":"Geometric Data-Driven Dimensionality Reduction in MPC with Guarantees","date":"2023-12-05","arxiv_id":"2312.02734","repositories_listed":0,"syntology":null},{"url":null,"slug":"analysis-and-mining-of-low-carbon-and-energy","title":"Analysis and mining of low-carbon and energy-saving tourism data characteristics based on machine learning algorithm","date":"2023-12-04","arxiv_id":"2312.03037","repositories_listed":0,"syntology":null},{"url":null,"slug":"relation-between-pls-and-ols-regression-in","title":"Relation between PLS and OLS regression in terms of the eigenvalue distribution of the regressor covariance matrix","date":"2023-12-03","arxiv_id":"2312.01379","repositories_listed":0,"syntology":null},{"url":null,"slug":"defining-reference-sequences-for-nocardia","title":"Defining Reference Sequences for Nocardia Species by Similarity and Clustering Analyses of 16S rRNA Gene Sequence Data","date":"2023-11-29","arxiv_id":"2311.17965","repositories_listed":0,"syntology":null},{"url":null,"slug":"linear-normalised-hash-function-for","title":"Linear normalised hash function for clustering gene sequences and identifying reference sequences from multiple sequence alignments","date":"2023-11-29","arxiv_id":"2311.17964","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-novel-deep-clustering-framework-for-fine","title":"A Novel Deep Clustering Framework for Fine-Scale Parcellation of Amygdala Using dMRI Tractography","date":"2023-11-25","arxiv_id":"2311.14935","repositories_listed":0,"syntology":null},{"url":null,"slug":"bridging-classical-and-quantum-machine","title":"Bridging Classical and Quantum Machine Learning: Knowledge Transfer From Classical to Quantum Neural Networks Using Knowledge Distillation","date":"2023-11-23","arxiv_id":"2311.13810","repositories_listed":0,"syntology":null},{"url":null,"slug":"detection-and-identification-accuracy-of-pca","title":"Detection and Identification Accuracy of PCA-Accelerated Real-Time Processing of Hyperspectral Imagery","date":"2023-11-23","arxiv_id":"2311.13779","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-learning-for-topological","title":"Unsupervised Learning for Topological Classification of Transportation Networks","date":"2023-11-23","arxiv_id":"2311.13887","repositories_listed":0,"syntology":null},{"url":null,"slug":"thinking-outside-the-box-orthogonal-approach","title":"Thinking Outside the Box: Orthogonal Approach to Equalizing Protected Attributes","date":"2023-11-21","arxiv_id":"2311.14733","repositories_listed":0,"syntology":null},{"url":null,"slug":"oddr-outlier-detection-dimension-reduction","title":"ODDR: Outlier Detection & Dimension Reduction Based Defense Against Adversarial Patches","date":"2023-11-20","arxiv_id":"2311.12084","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-improved-neural-network-model-based-on-cnn","title":"An Improved CNN-based Neural Network Model for Fruit Sugar Level Detection","date":"2023-11-18","arxiv_id":"2311.11120","repositories_listed":0,"syntology":null},{"url":null,"slug":"bit-cipher-a-simple-yet-powerful-word","title":"Bit Cipher -- A Simple yet Powerful Word Representation System that Integrates Efficiently with Language Models","date":"2023-11-18","arxiv_id":"2311.11012","repositories_listed":0,"syntology":null},{"url":null,"slug":"classification-methods-based-on-machine","title":"Classification Methods Based on Machine Learning for the Analysis of Fetal Health Data","date":"2023-11-18","arxiv_id":"2311.10962","repositories_listed":0,"syntology":null},{"url":null,"slug":"handling-overlapping-asymmetric-datasets-a","title":"Handling Overlapping Asymmetric Datasets -- A Twice Penalized P-Spline Approach","date":"2023-11-17","arxiv_id":"2311.10489","repositories_listed":0,"syntology":null},{"url":null,"slug":"utilizing-vq-vae-for-end-to-end-health","title":"Utilizing VQ-VAE for End-to-End Health Indicator Generation in Predicting Rolling Bearing RUL","date":"2023-11-17","arxiv_id":"2311.10525","repositories_listed":0,"syntology":null},{"url":null,"slug":"finding-real-world-orbital-motion-laws-from","title":"Finding Real-World Orbital Motion Laws from Data","date":"2023-11-16","arxiv_id":"2311.10012","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-pretext-to-purpose-batch-adaptive-self","title":"From Pretext to Purpose: Batch-Adaptive Self-Supervised Learning","date":"2023-11-16","arxiv_id":"2311.09974","repositories_listed":0,"syntology":null},{"url":null,"slug":"simple-but-effective-unsupervised","title":"Simple but Effective Unsupervised Classification for Specified Domain Images: A Case Study on Fungi Images","date":"2023-11-15","arxiv_id":"2311.08995","repositories_listed":0,"syntology":null},{"url":null,"slug":"high-dimensional-binary-choice-model-with","title":"High Dimensional Binary Choice Model with Unknown Heteroskedasticity or Instrumental Variables","date":"2023-11-13","arxiv_id":"2311.07067","repositories_listed":0,"syntology":null},{"url":null,"slug":"cricket-player-profiling-unraveling-strengths","title":"Cricket Player Profiling: Unraveling Strengths and Weaknesses Using Text Commentary Data","date":"2023-11-12","arxiv_id":"2311.06818","repositories_listed":0,"syntology":null},{"url":null,"slug":"inference-and-interference-the-role-of","title":"Inference and Interference: The Role of Clipping, Pruning and Loss Landscapes in Differentially Private Stochastic Gradient Descent","date":"2023-11-12","arxiv_id":"2311.06839","repositories_listed":0,"syntology":null},{"url":null,"slug":"covering-number-of-real-algebraic-varieties","title":"Covering Number of Real Algebraic Varieties and Beyond: Improved Bounds and Applications","date":"2023-11-09","arxiv_id":"2311.05116","repositories_listed":0,"syntology":null},{"url":null,"slug":"perfecting-liquid-state-theories-with-machine","title":"Perfecting Liquid-State Theories with Machine Intelligence","date":"2023-11-09","arxiv_id":"2311.05167","repositories_listed":0,"syntology":null},{"url":null,"slug":"computing-approximate-ell-p-sensitivities","title":"Computing Approximate $\\ell_p$ Sensitivities","date":"2023-11-07","arxiv_id":"2311.04158","repositories_listed":0,"syntology":null},{"url":null,"slug":"manifold-learning-what-how-and-why","title":"Manifold learning: what, how, and why","date":"2023-11-07","arxiv_id":"2311.03757","repositories_listed":0,"syntology":null},{"url":null,"slug":"3-dimensional-residual-neural-architecture","title":"3-Dimensional residual neural architecture search for ultrasonic defect detection","date":"2023-11-03","arxiv_id":"2311.01867","repositories_listed":0,"syntology":null},{"url":null,"slug":"tailorme-self-supervised-learning-of-an","title":"TailorMe: Self-Supervised Learning of an Anatomically Constrained Volumetric Human Shape Model","date":"2023-11-03","arxiv_id":"2312.02173","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-collective-behaviors-from","title":"Learning Collective Behaviors from Observation","date":"2023-11-01","arxiv_id":"2311.00875","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-compressed-learning-for-3d-seismic","title":"Deep Compressed Learning for 3D Seismic Inversion","date":"2023-10-31","arxiv_id":"2311.00107","repositories_listed":0,"syntology":null},{"url":null,"slug":"gauge-optimal-approximate-learning-for-small","title":"Gauge-optimal approximate learning for small data classification problems","date":"2023-10-29","arxiv_id":"2310.19066","repositories_listed":0,"syntology":null},{"url":null,"slug":"low-dimensional-gradient-helps-out-of","title":"Low-Dimensional Gradient Helps Out-of-Distribution Detection","date":"2023-10-26","arxiv_id":"2310.17163","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-stress-fields-for-reduced-order","title":"Neural Stress Fields for Reduced-order Elastoplasticity and Fracture","date":"2023-10-26","arxiv_id":"2310.17790","repositories_listed":0,"syntology":null},{"url":null,"slug":"instance-wise-linearization-of-neural-network","title":"Instance-wise Linearization of Neural Network for Model Interpretation","date":"2023-10-25","arxiv_id":"2310.16295","repositories_listed":0,"syntology":null},{"url":null,"slug":"nonlinear-dimensionality-reduction-then-and","title":"Nonlinear dimensionality reduction then and now: AIMs for dissipative PDEs in the ML era","date":"2023-10-24","arxiv_id":"2310.15816","repositories_listed":0,"syntology":null},{"url":null,"slug":"k-nearest-neighbors-induced-topological-pca","title":"K-Nearest-Neighbors Induced Topological PCA for scRNA Sequence Data Analysis","date":"2023-10-23","arxiv_id":"2310.14521","repositories_listed":0,"syntology":null},{"url":null,"slug":"noise-robust-latent-vector-reconstruction-in","title":"Noise-robust latent vector reconstruction in ptychography using deep generative models","date":"2023-10-18","arxiv_id":"2311.07580","repositories_listed":0,"syntology":null}],"record_sha256":"20dbec976048db04977895857a32f99fe48ab3f9844cdddc66c23950d7288cef","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}