{"total":21,"rows":[{"id":"2107.06929","title":"Feature Shift Detection: Localizing Which Features Have Shifted via Conditional Distribution Tests","created":"2021-07-14","cited_by_count":24,"area":null},{"id":"2305.02164","title":"Nonparametric Generative Modeling with Conditional Sliced-Wasserstein Flows","created":"2023-05-03","cited_by_count":15,"area":null},{"id":"2502.09346","title":"Machine learning for modelling unstructured grid data in computational physics: a review","created":"2025-02-13","cited_by_count":12,"area":null},{"id":"2406.15747","title":"Modeling Unknown Stochastic Dynamical System Subject to External Excitation","created":"2024-06-22","cited_by_count":7,"area":null},{"id":"2204.08415","title":"Exploring Dimensionality Reduction Techniques in Multilingual Transformers","created":"2022-04-18","cited_by_count":6,"area":null},{"id":"2505.00685","title":"On the Importance of Gaussianizing Representations","created":"2025-05-01","cited_by_count":6,"area":null},{"id":"2306.13520","title":"On the Convergence Rate of Gaussianization with Random Rotations","created":"2023-06-23","cited_by_count":5,"area":null},{"id":"2104.07232","title":"Iterative Alignment Flows","created":"2021-04-15","cited_by_count":4,"area":null},{"id":"2204.05699","title":"Unsupervised Anomaly and Change Detection with Multivariate Gaussianization","created":"2022-04-12","cited_by_count":2,"area":null},{"id":"2206.03860","title":"Orthonormal Convolutions for the Rotation Based Iterative Gaussianization","created":"2022-06-08","cited_by_count":2,"area":null},{"id":"2303.09874","title":"Image Statistics Predict the Sensitivity of Perceptual Quality Metrics","created":"2023-03-17","cited_by_count":1,"area":null},{"id":"2507.01726","title":"Generative flow-based warm start of the variational quantum eigensolver","created":"2025-07-02","cited_by_count":1,"area":null},{"id":"2510.07732","title":"Rotated Mean-Field Variational Inference and Iterative Gaussianization","created":"2025-10-09","cited_by_count":1,"area":null},{"id":"2307.14839","title":"Kernelised Normalising Flows","created":"2023-07-27","cited_by_count":0,"area":null},{"id":"2310.16777","title":"MixerFlow: MLP-Mixer meets Normalising Flows","created":"2023-10-25","cited_by_count":0,"area":null},{"id":"2403.10390","title":"Evaluating Perceptual Distance Models by Fitting Binomial Distributions to Two-Alternative Forced Choice Data","created":"2024-03-15","cited_by_count":0,"area":null},{"id":"2510.02056","title":"Adaptive Heterogeneous Mixtures of Normalising Flows for Robust Variational Inference","created":"2025-10-02","cited_by_count":0,"area":null},{"id":"2510.17120","title":"Matricial Free Energy as a Gaussianizing Regularizer: Enhancing Autoencoders for Gaussian Code Generation","created":"2025-10-20","cited_by_count":0,"area":null},{"id":"2607.03809","title":"Stable Global Weighting of Flow Mixtures using Simplex Exponential Moving Average","created":"2026-07-04","cited_by_count":0,"area":null},{"id":"2607.14081","title":"Linear Independent Component Analysis via Optimal Transport","created":"2026-07-15","cited_by_count":0,"area":null},{"id":"2609.11253","title":"MUtE: A Dual Framework for Concept Erasure and Counterfactual Interventions","created":"2026-09-10","cited_by_count":0,"area":null}],"next_cursor":null}