{"total":108,"rows":[{"id":"2209.00796","title":"Diffusion Models: A Comprehensive Survey of Methods and Applications","created":"2022-09-02","cited_by_count":1114,"area":"diffusion"},{"id":"2302.03169","title":"Data Selection for Language Models via Importance Resampling","created":"2023-02-06","cited_by_count":329,"area":null},{"id":"2211.17091","title":"Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models","created":"2022-11-28","cited_by_count":100,"area":"diffusion"},{"id":"2210.06662","title":"Action Matching: Learning Stochastic Dynamics from Samples","created":"2022-10-13","cited_by_count":98,"area":null},{"id":"2111.11010","title":"Density Ratio Estimation via Infinitesimal Classification","created":"2021-11-22","cited_by_count":61,"area":null},{"id":"2107.00643","title":"Mandoline: Model Evaluation under Distribution Shift","created":"2021-07-01","cited_by_count":55,"area":null},{"id":"2209.14249","title":"Compositional Score Modeling for Simulation-based Inference","created":"2022-09-28","cited_by_count":48,"area":null},{"id":"2107.02212","title":"Featurized Density Ratio Estimation","created":"2021-07-05","cited_by_count":33,"area":null},{"id":"2310.09031","title":"MINDE: Mutual Information Neural Diffusion Estimation","created":"2023-10-13","cited_by_count":31,"area":null},{"id":"2106.13401","title":"Decomposed Mutual Information Estimation for Contrastive Representation Learning","created":"2021-06-25","cited_by_count":25,"area":null},{"id":"2403.01189","title":"Training Unbiased Diffusion Models From Biased Dataset","created":"2024-03-02","cited_by_count":25,"area":"diffusion"},{"id":"2302.02913","title":"Beyond Statistical Similarity: Rethinking Metrics for Deep Generative Models in Engineering Design","created":"2023-02-06","cited_by_count":23,"area":"diffusion"},{"id":"2403.02187","title":"Mutual Information Estimation via Normalizing Flows","created":"2024-03-04","cited_by_count":22,"area":null},{"id":"2209.08739","title":"Adaptive Multi-stage Density Ratio Estimation for Learning Latent Space Energy-based Model","created":"2022-09-19","cited_by_count":18,"area":null},{"id":"2305.00869","title":"Estimating the Density Ratio between Distributions with High Discrepancy using Multinomial Logistic Regression","created":"2023-05-01","cited_by_count":17,"area":null},{"id":"2110.11271","title":"Analyzing and Improving the Optimization Landscape of Noise-Contrastive Estimation","created":"2021-10-21","cited_by_count":15,"area":null},{"id":"2403.10175","title":"A Short Survey on Importance Weighting for Machine Learning","created":"2024-03-15","cited_by_count":15,"area":null},{"id":"2408.04154","title":"The Data Addition Dilemma","created":"2024-08-08","cited_by_count":15,"area":null},{"id":"2202.04933","title":"Energy-Based Contrastive Learning of Visual Representations","created":"2022-02-10","cited_by_count":13,"area":null},{"id":"2305.10994","title":"Graphical vs. Deep Generative Models: Measuring the Impact of Differentially Private Mechanisms and Budgets on Utility","created":"2023-05-18","cited_by_count":13,"area":null},{"id":"2502.02300","title":"Density Ratio Estimation with Conditional Probability Paths","created":"2025-02-04","cited_by_count":13,"area":null},{"id":"2306.15166","title":"Constraining Generative Models for Engineering Design with Negative Data","created":"2023-06-27","cited_by_count":11,"area":null},{"id":"2405.17880","title":"Diffusion Rejection Sampling","created":"2024-05-28","cited_by_count":11,"area":"diffusion"},{"id":"2409.20547","title":"Annealing Flow Generative Models Towards Sampling High-Dimensional and Multi-Modal Distributions","created":"2024-09-30","cited_by_count":11,"area":null},{"id":"2505.05034","title":"Dequantified Diffusion-Schr{\\\"o}dinger Bridge for Density Ratio Estimation","created":"2025-05-08","cited_by_count":11,"area":null},{"id":"2110.15397","title":"A Computationally Efficient Method for Learning Exponential Family Distributions","created":"2021-10-28","cited_by_count":10,"area":null},{"id":"2405.16876","title":"Transfer Learning for Diffusion Models","created":"2024-05-27","cited_by_count":10,"area":"diffusion"},{"id":"2509.01657","title":"Data Retrieval with Importance Weights for Few-Shot Imitation Learning","created":"2025-09-01","cited_by_count":10,"area":"offlinerl"},{"id":"2509.22122","title":"Direct Bias-Correction Term Estimation for Average Treatment Effect Estimation","created":"2025-09-26","cited_by_count":9,"area":null},{"id":"2305.11857","title":"Computing high-dimensional optimal transport by flow neural networks","created":"2023-05-19","cited_by_count":8,"area":null},{"id":"2305.15577","title":"Minimizing $f$-Divergences by Interpolating Velocity Fields","created":"2023-05-24","cited_by_count":8,"area":null},{"id":"2405.16730","title":"\"Noisier\" Noise Contrastive Eestimation is (Almost) Maximum Likelihood","created":"2024-05-27","cited_by_count":8,"area":null},{"id":"2405.20759","title":"Information Theoretic Text-to-Image Alignment","created":"2024-05-31","cited_by_count":8,"area":"diffusion"},{"id":"2406.18806","title":"Density Ratio Estimation via Sampling along Generalized Geodesics on Statistical Manifolds","created":"2024-06-27","cited_by_count":8,"area":null},{"id":"2411.03014","title":"Your copula is a classifier in disguise: classification-based copula density estimation","created":"2024-11-05","cited_by_count":8,"area":null},{"id":"2205.08340","title":"A unified framework for dataset shift diagnostics","created":"2022-05-17","cited_by_count":7,"area":null},{"id":"2306.00608","title":"On the Effectiveness of Hybrid Mutual Information Estimation","created":"2023-06-01","cited_by_count":7,"area":null},{"id":"2405.07822","title":"Synthetic Tabular Data Validation: A Divergence-Based Approach","created":"2024-05-13","cited_by_count":7,"area":null},{"id":"2502.01383","title":"InfoBridge: Mutual Information estimation via Bridge Matching","created":"2025-02-03","cited_by_count":7,"area":null},{"id":"2507.00846","title":"BoltzNCE: Learning Likelihoods for Boltzmann Generation with Stochastic Interpolants and Noise Contrastive Estimation","created":"2025-07-01","cited_by_count":7,"area":null},{"id":"2509.19707","title":"Diffusion and Flow-based Copulas: Forgetting and Remembering Dependencies","created":"2025-09-24","cited_by_count":7,"area":null},{"id":"2510.24433","title":"Nearest Neighbor Matching as Least Squares Density Ratio Estimation and Riesz Regression","created":"2025-10-28","cited_by_count":7,"area":null},{"id":"2107.00801","title":"Meta-Learning for Relative Density-Ratio Estimation","created":"2021-07-02","cited_by_count":6,"area":null},{"id":"2210.00189","title":"Pitfalls of Gaussians as a noise distribution in NCE","created":"2022-10-01","cited_by_count":6,"area":null},{"id":"2306.07485","title":"Learning Unnormalized Statistical Models via Compositional Optimization","created":"2023-06-13","cited_by_count":6,"area":null},{"id":"2310.16638","title":"Double Debiased Covariate Shift Adaptation Robust to Density-Ratio Estimation","created":"2023-10-25","cited_by_count":6,"area":null},{"id":"2603.02196","title":"Conformal Policy Control","created":"2026-03-02","cited_by_count":6,"area":null},{"id":"2112.03440","title":"A Unified Framework for Multi-distribution Density Ratio Estimation","created":"2021-12-07","cited_by_count":5,"area":null},{"id":"2204.13999","title":"Statistical applications of contrastive learning","created":"2022-04-29","cited_by_count":5,"area":null},{"id":"2402.13891","title":"Overcoming Saturation in Density Ratio Estimation by Iterated Regularization","created":"2024-02-21","cited_by_count":5,"area":null},{"id":"2407.08946","title":"Your Diffusion Model is Secretly a Noise Classifier and Benefits from Contrastive Training","created":"2024-07-12","cited_by_count":5,"area":"diffusion"},{"id":"2506.00866","title":"Projection Pursuit Density Ratio Estimation","created":"2025-06-01","cited_by_count":5,"area":null},{"id":"2507.10425","title":"Non-exchangeable Conformal Prediction with Optimal Transport: Tackling Distribution Shifts with Unlabeled Data","created":"2025-07-14","cited_by_count":5,"area":null},{"id":"2509.25837","title":"Distillation of Large Language Models via Concrete Score Matching","created":"2025-09-30","cited_by_count":5,"area":null},{"id":"2510.23534","title":"Direct Debiased Machine Learning via Bregman Divergence Minimization","created":"2025-10-27","cited_by_count":5,"area":null},{"id":"2206.03955","title":"Out-of-Distribution Detection with Class Ratio Estimation","created":"2022-06-08","cited_by_count":4,"area":null},{"id":"2206.14439","title":"Approximate Data Deletion in Generative Models","created":"2022-06-29","cited_by_count":4,"area":null},{"id":"2302.10260","title":"Unsupervised Learning on a DIET: Datum IndEx as Target Free of Self-Supervision, Reconstruction, Projector Head","created":"2023-02-20","cited_by_count":4,"area":null},{"id":"2405.19553","title":"Convergence Bounds for Sequential Monte Carlo on Multimodal Distributions using Soft Decomposition","created":"2024-05-29","cited_by_count":4,"area":null},{"id":"2410.16636","title":"General Frameworks for Conditional Two-Sample Testing","created":"2024-10-22","cited_by_count":4,"area":null},{"id":"2510.20968","title":"Neural Mutual Information Estimation with Vector Copulas","created":"2025-10-23","cited_by_count":4,"area":null},{"id":"2511.08552","title":"FMMI: Flow Matching Mutual Information Estimation","created":"2025-11-11","cited_by_count":4,"area":"diffusion"},{"id":"2103.02740","title":"Contrastive learning of strong-mixing continuous-time stochastic processes","created":"2021-03-03","cited_by_count":3,"area":null},{"id":"2111.13226","title":"A Kernel Test for Causal Association via Noise Contrastive Backdoor Adjustment","created":"2021-11-25","cited_by_count":3,"area":null},{"id":"2310.01808","title":"Simulation-based Inference with the Generalized Kullback-Leibler Divergence","created":"2023-10-03","cited_by_count":3,"area":null},{"id":"2509.04852","title":"Diffusion Secant Alignment for Score-Based Density Ratio Estimation","created":"2025-09-05","cited_by_count":3,"area":null},{"id":"2509.20609","title":"MMG: Mutual Information Estimation via the MMSE Gap in Diffusion","created":"2025-09-24","cited_by_count":3,"area":"diffusion"},{"id":"2511.04568","title":"Riesz Regression As Direct Density Ratio Estimation","created":"2025-11-06","cited_by_count":3,"area":null},{"id":"2512.15036","title":"Spectral Representation-based Reinforcement Learning","created":"2025-12-17","cited_by_count":3,"area":"deeprl"},{"id":"2602.00834","title":"A Minimum Variance Path Principle for Accurate and Stable Score-Based Density Ratio Estimation","created":"2026-01-31","cited_by_count":3,"area":null},{"id":"2103.05276","title":"Continual Density Ratio Estimation in an Online Setting","created":"2021-03-09","cited_by_count":2,"area":null},{"id":"2112.03638","title":"Scaling Structured Inference with Randomization","created":"2021-12-07","cited_by_count":2,"area":null},{"id":"2301.09696","title":"Optimizing the Noise in Self-Supervised Learning: from Importance Sampling to Noise-Contrastive Estimation","created":"2023-01-23","cited_by_count":2,"area":null},{"id":"2302.09810","title":"Toward Asymptotic Optimality: Sequential Unsupervised Regression of Density Ratio for Early Classification","created":"2023-02-20","cited_by_count":2,"area":null},{"id":"2303.03714","title":"Generative Modeling with Flow-Guided Density Ratio Learning","created":"2023-03-07","cited_by_count":2,"area":null},{"id":"2306.00872","title":"Is novelty predictable?","created":"2023-06-01","cited_by_count":2,"area":null},{"id":"2309.06413","title":"On Computationally Efficient Learning of Exponential Family Distributions","created":"2023-09-12","cited_by_count":2,"area":null},{"id":"2402.10095","title":"Classification Diffusion Models: Revitalizing Density Ratio Estimation","created":"2024-02-15","cited_by_count":2,"area":"diffusion"},{"id":"2406.03680","title":"Meta-learning for Positive-unlabeled Classification","created":"2024-06-06","cited_by_count":2,"area":null},{"id":"2407.01371","title":"Binary Losses for Density Ratio Estimation","created":"2024-07-01","cited_by_count":2,"area":null},{"id":"2502.13394","title":"Flow-based generative models as iterative algorithms in probability space","created":"2025-02-19","cited_by_count":2,"area":null},{"id":"2502.19183","title":"INFO-SEDD: Continuous Time Markov Chains as Scalable Information Metrics Estimators","created":"2025-02-26","cited_by_count":2,"area":null},{"id":"2503.20767","title":"Reliable algorithm selection for machine learning-guided design","created":"2025-03-26","cited_by_count":2,"area":null},{"id":"2510.26783","title":"A Unified Theory for Causal Inference: Direct Debiased Machine Learning via Bregman-Riesz Regression","created":"2025-10-30","cited_by_count":2,"area":null},{"id":"2604.18239","title":"Towards Disentangled Preference Optimization Dynamics: Suppress the Loser, Preserve the Winner","created":"2026-04-20","cited_by_count":2,"area":"alignment"},{"id":"2605.26850","title":"Learning Energy-Based Models from Stochastic Interpolants using Spatiotemporal Differences","created":"2026-05-26","cited_by_count":2,"area":null},{"id":"2606.11949","title":"Online Shift Detection and Conformal Adaptation for Deployed Safety Classifiers","created":"2026-06-10","cited_by_count":2,"area":"lr"},{"id":"2402.02041","title":"Alpha-divergence loss function for neural density ratio estimation","created":"2024-02-03","cited_by_count":1,"area":null},{"id":"2407.15687","title":"SoftCVI: Contrastive variational inference with self-generated soft labels","created":"2024-07-22","cited_by_count":1,"area":null},{"id":"2508.03059","title":"Two-sample comparison through additive tree models for density ratios","created":"2025-08-05","cited_by_count":1,"area":null},{"id":"2511.08303","title":"Semi-Supervised Treatment Effect Estimation with Unlabeled Covariates for Prediction-Powered Causal Inference","created":"2025-11-11","cited_by_count":1,"area":null},{"id":"2604.10672","title":"One-Step Score-Based Density Ratio Estimation","created":"2026-04-12","cited_by_count":1,"area":null},{"id":"2201.13127","title":"Unified Perspective on Probability Divergence via Maximum Likelihood Density Ratio Estimation: Bridging KL-Divergence and Integral Probability Metrics","created":"2022-01-31","cited_by_count":0,"area":null},{"id":"2305.15612","title":"Density Ratio Estimation-based Bayesian Optimization with Semi-Supervised Learning","created":"2023-05-24","cited_by_count":0,"area":null},{"id":"2310.08762","title":"Stabilizing Subject Transfer in EEG Classification with Divergence Estimation","created":"2023-10-12","cited_by_count":0,"area":null},{"id":"2406.09084","title":"Operator-Informed Score Matching for Markov Diffusion Models","created":"2024-06-13","cited_by_count":0,"area":"diffusion"},{"id":"2506.15505","title":"Time-dependent density estimation using binary classifiers","created":"2025-06-18","cited_by_count":0,"area":null},{"id":"2506.18764","title":"Neural Total Variation Distance Estimators for Changepoint Detection in News Data","created":"2025-06-23","cited_by_count":0,"area":null},{"id":"2510.16127","title":"Learning density ratios in causal inference using Bregman-Riesz regression","created":"2025-10-17","cited_by_count":0,"area":null},{"id":"2512.09266","title":"Robust and Sparse Estimation of Unbounded Density Ratio under Heavy Contamination","created":"2025-12-10","cited_by_count":0,"area":null}],"next_cursor":"100"}