{"total":21,"rows":[{"id":"2402.17641","title":"Variational Learning is Effective for Large Deep Networks","created":"2024-02-27","cited_by_count":65,"area":null},{"id":"2211.06291","title":"Do Bayesian Neural Networks Need To Be Fully Stochastic?","created":"2022-11-11","cited_by_count":63,"area":null},{"id":"2203.16481","title":"On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification","created":"2022-03-30","cited_by_count":46,"area":null},{"id":"2202.10847","title":"UncertaINR: Uncertainty Quantification of End-to-End Implicit Neural Representations for Computed Tomography","created":"2022-02-22","cited_by_count":19,"area":null},{"id":"2205.13900","title":"How Tempering Fixes Data Augmentation in Bayesian Neural Networks","created":"2022-05-27","cited_by_count":13,"area":null},{"id":"2210.07612","title":"Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes","created":"2022-10-14","cited_by_count":11,"area":null},{"id":"2304.01762","title":"Incorporating Unlabelled Data into Bayesian Neural Networks","created":"2023-04-04","cited_by_count":9,"area":null},{"id":"2506.10060","title":"Textual Bayes: Quantifying Prompt Uncertainty in LLM-Based Systems","created":"2025-06-11","cited_by_count":8,"area":null},{"id":"2303.05796","title":"Training, Architecture, and Prior for Deterministic Uncertainty Methods","created":"2023-03-10","cited_by_count":7,"area":null},{"id":"2206.12361","title":"Robustness to corruption in pre-trained Bayesian neural networks","created":"2022-06-24","cited_by_count":5,"area":null},{"id":"2207.03859","title":"Variational Inference of overparameterized Bayesian Neural Networks: a theoretical and empirical study","created":"2022-07-08","cited_by_count":5,"area":null},{"id":"2403.01272","title":"Can a Confident Prior Replace a Cold Posterior?","created":"2024-03-02","cited_by_count":5,"area":null},{"id":"2410.21702","title":"Minimax optimality of deep neural networks on dependent data via PAC-Bayes bounds","created":"2024-10-29","cited_by_count":4,"area":null},{"id":"2206.11173","title":"Cold Posteriors through PAC-Bayes","created":"2022-06-22","cited_by_count":3,"area":null},{"id":"2309.05292","title":"The fine print on tempered posteriors","created":"2023-09-11","cited_by_count":3,"area":null},{"id":"2310.01189","title":"If there is no underfitting, there is no Cold Posterior Effect","created":"2023-10-02","cited_by_count":2,"area":null},{"id":"2405.18351","title":"Evaluating Bayesian deep learning for radio galaxy classification","created":"2024-05-28","cited_by_count":2,"area":null},{"id":"2503.00699","title":"Parameter Expanded Stochastic Gradient Markov Chain Monte Carlo","created":"2025-03-02","cited_by_count":2,"area":null},{"id":"2512.02823","title":"Tempering the Bayes Filter towards Improved Model-Based Estimation","created":"2025-12-02","cited_by_count":1,"area":null},{"id":"2511.01628","title":"Partial Trace-Class Bayesian Neural Networks","created":"2025-11-03","cited_by_count":0,"area":null},{"id":"2606.25745","title":"Gaussian Mean Field Variational Inference can Overestimate Predictive Variance","created":"2026-06-24","cited_by_count":0,"area":null}],"next_cursor":null}