{"total":15,"rows":[{"id":"2101.05036","title":"Estimating and Evaluating Regression Predictive Uncertainty in Deep Object Detectors","created":"2021-01-13","cited_by_count":37,"area":null},{"id":"2112.08217","title":"Probabilistic Forecasting with Generative Networks via Scoring Rule Minimization","created":"2021-12-15","cited_by_count":37,"area":null},{"id":"2305.16274","title":"Non-adversarial training of Neural SDEs with signature kernel scores","created":"2023-05-25","cited_by_count":37,"area":null},{"id":"2205.15784","title":"Likelihood-Free Inference with Generative Neural Networks via Scoring Rule Minimization","created":"2022-05-31","cited_by_count":15,"area":null},{"id":"2211.13724","title":"Estimating Regression Predictive Distributions with Sample Networks","created":"2022-11-24","cited_by_count":4,"area":null},{"id":"2410.03973","title":"Efficient Training of Neural Stochastic Differential Equations by Matching Finite Dimensional Distributions","created":"2024-10-04","cited_by_count":4,"area":null},{"id":"2410.07066","title":"A Gentle Introduction and Tutorial on Deep Generative Models in Transportation Research","created":"2024-10-09","cited_by_count":4,"area":null},{"id":"2209.08418","title":"Sample-based Uncertainty Quantification with a Single Deterministic Neural Network","created":"2022-09-17","cited_by_count":3,"area":null},{"id":"2303.08909","title":"Latent-Conditioned Policy Gradient for Multi-Objective Deep Reinforcement Learning","created":"2023-03-15","cited_by_count":1,"area":null},{"id":"2512.16383","title":"Multivariate Uncertainty Quantification with Tomographic Quantile Forests","created":"2025-12-18","cited_by_count":1,"area":null},{"id":"2504.17622","title":"Likelihood-Free Variational Autoencoders","created":"2025-04-24","cited_by_count":0,"area":null},{"id":"2504.18522","title":"Extrapolation Guarantees for Perturbation Modeling Under the Additive Latent Shift Assumption","created":"2025-04-25","cited_by_count":0,"area":null},{"id":"2509.25507","title":"One-shot Conditional Sampling: MMD meets Nearest Neighbors","created":"2025-09-29","cited_by_count":0,"area":null},{"id":"2606.19496","title":"Calibrating Generative Models to Feature Distributions with MMD Finetuning","created":"2026-06-17","cited_by_count":0,"area":null},{"id":"2607.05240","title":"Optimizing ML Workload Partitioning between CPUs and CIM Accelerators for Heterogeneous Computing","created":"2026-07-06","cited_by_count":0,"area":null}],"next_cursor":null}