{"total":24,"rows":[{"id":"2203.09410","title":"A Framework and Benchmark for Deep Batch Active Learning for Regression","created":"2022-03-17","cited_by_count":49,"area":null},{"id":"2205.00403","title":"A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness","created":"2022-05-01","cited_by_count":49,"area":null},{"id":"2210.12642","title":"Accelerated Linearized Laplace Approximation for Bayesian Deep Learning","created":"2022-10-23","cited_by_count":28,"area":null},{"id":"2307.03217","title":"Quantification of Uncertainty with Adversarial Models","created":"2023-07-06","cited_by_count":28,"area":null},{"id":"2207.06873","title":"BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks","created":"2022-07-14","cited_by_count":23,"area":null},{"id":"2304.02902","title":"Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry","created":"2023-04-06","cited_by_count":21,"area":null},{"id":"2210.04994","title":"Sampling-based inference for large linear models, with application to linearised Laplace","created":"2022-10-10","cited_by_count":18,"area":null},{"id":"2306.07158","title":"Riemannian Laplace approximations for Bayesian neural networks","created":"2023-06-12","cited_by_count":15,"area":null},{"id":"2205.10041","title":"Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks","created":"2022-05-20","cited_by_count":14,"area":null},{"id":"2502.02870","title":"Uncertainty Quantification with the Empirical Neural Tangent Kernel","created":"2025-02-05","cited_by_count":11,"area":null},{"id":"2304.08309","title":"Promises and Pitfalls of the Linearized Laplace in Bayesian Optimization","created":"2023-04-17","cited_by_count":10,"area":null},{"id":"2311.11096","title":"On the Out of Distribution Robustness of Foundation Models in Medical Image Segmentation","created":"2023-11-18","cited_by_count":6,"area":null},{"id":"2411.18425","title":"Streamlining Prediction in Bayesian Deep Learning","created":"2024-11-27","cited_by_count":5,"area":null},{"id":"2507.17013","title":"laplax -- Laplace Approximations with JAX","created":"2025-07-22","cited_by_count":5,"area":null},{"id":"2404.01801","title":"EventSleep: Sleep Activity Recognition with Event Cameras","created":"2024-04-02","cited_by_count":3,"area":null},{"id":"2503.15367","title":"FedBEns: One-Shot Federated Learning based on Bayesian Ensemble","created":"2025-03-19","cited_by_count":3,"area":null},{"id":"2604.03388","title":"Scalable Variational Bayesian Fine-Tuning of LLMs via Orthogonalized Low-Rank Adapters","created":"2026-04-03","cited_by_count":2,"area":null},{"id":"2406.15664","title":"Flat Posterior Does Matter For Bayesian Model Averaging","created":"2024-06-21","cited_by_count":1,"area":null},{"id":"2505.13585","title":"Scalable Bayesian Monte Carlo: fast uncertainty estimation beyond deep ensembles","created":"2025-05-19","cited_by_count":1,"area":null},{"id":"2512.01500","title":"Walking on the Fiber: A Simple Geometric Approximation for Bayesian Neural Networks","created":"2025-12-01","cited_by_count":1,"area":null},{"id":"2503.13296","title":"On Local Posterior Structure in Deep Ensembles","created":"2025-03-17","cited_by_count":0,"area":null},{"id":"2504.13465","title":"Are you SURE? Enhancing Multimodal Pretraining with Missing Modalities through Uncertainty Estimation","created":"2025-04-18","cited_by_count":0,"area":null},{"id":"2507.20718","title":"Uncertainty-driven Embedding Convolution","created":"2025-07-28","cited_by_count":0,"area":null},{"id":"2607.18965","title":"Variational meta-learning inference for low dimensional neural system identification","created":"2026-07-21","cited_by_count":0,"area":null}],"next_cursor":null}