{"total":32,"rows":[{"id":"2402.15406","title":"Conformalized-DeepONet: A Distribution-Free Framework for Uncertainty Quantification in Deep Operator Networks","created":"2024-02-23","cited_by_count":28,"area":null},{"id":"2211.10575","title":"Bayesian autoencoders for data-driven discovery of coordinates, governing equations and fundamental constants","created":"2022-11-19","cited_by_count":24,"area":null},{"id":"2111.02484","title":"Accelerated replica exchange stochastic gradient Langevin diffusion enhanced Bayesian DeepONet for solving noisy parametric PDEs","created":"2021-11-03","cited_by_count":22,"area":null},{"id":"2112.05120","title":"On Convergence of Federated Averaging Langevin Dynamics","created":"2021-12-09","cited_by_count":14,"area":null},{"id":"2105.13937","title":"Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks","created":"2021-05-28","cited_by_count":11,"area":null},{"id":"2212.07959","title":"Scalable Bayesian Uncertainty Quantification for Neural Network Potentials: Promise and Pitfalls","created":"2022-12-15","cited_by_count":11,"area":null},{"id":"2306.00810","title":"Deep Operator Learning-based Surrogate Models with Uncertainty Quantification for Optimizing Internal Cooling Channel Rib Profiles","created":"2023-06-01","cited_by_count":10,"area":null},{"id":"2401.11665","title":"Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo","created":"2024-01-22","cited_by_count":10,"area":null},{"id":"2202.09867","title":"Interacting Contour Stochastic Gradient Langevin Dynamics","created":"2022-02-20","cited_by_count":9,"area":null},{"id":"2402.17699","title":"Gradient-based Discrete Sampling with Automatic Cyclical Scheduling","created":"2024-02-27","cited_by_count":9,"area":null},{"id":"2103.08640","title":"UPANets: Learning from the Universal Pixel Attention Networks","created":"2021-03-15","cited_by_count":7,"area":null},{"id":"2211.10837","title":"Non-reversible Parallel Tempering for Deep Posterior Approximation","created":"2022-11-20","cited_by_count":7,"area":null},{"id":"2405.07839","title":"Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin Dynamics","created":"2024-05-13","cited_by_count":7,"area":null},{"id":"2503.19066","title":"Accelerating Langevin Monte Carlo Sampling: A Large Deviations Analysis","created":"2025-03-24","cited_by_count":4,"area":null},{"id":"2407.04400","title":"Hard-Attention Gates with Gradient Routing for Endoscopic Image Computing","created":"2024-07-05","cited_by_count":3,"area":null},{"id":"2509.00663","title":"Morephy-Net: An Evolutionary Multi-objective Optimization for Replica-Exchange-based Physics-informed Neural Operator Learning Networks","created":"2025-08-31","cited_by_count":3,"area":null},{"id":"2502.00550","title":"Active Learning with Bayesian Multi-Fidelity Laplace Neural Operators for Oscillatory Parametric PDEs","created":"2025-02-01","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":"2305.13882","title":"Subsampling Error in Stochastic Gradient Langevin Diffusions","created":"2023-05-23","cited_by_count":1,"area":null},{"id":"2311.16519","title":"B-LSTM-MIONet: Bayesian LSTM-based Neural Operators for Learning the Response of Complex Dynamical Systems to Length-Variant Multiple Input Functions","created":"2023-11-28","cited_by_count":1,"area":null},{"id":"2502.18300","title":"Bayesian Computation in Deep Learning","created":"2025-02-25","cited_by_count":1,"area":null},{"id":"2502.19240","title":"Enhancing Gradient-based Discrete Sampling via Parallel Tempering","created":"2025-02-26","cited_by_count":1,"area":null},{"id":"2505.11190","title":"JaxSGMC: Modular stochastic gradient MCMC in JAX","created":"2025-05-16","cited_by_count":1,"area":null},{"id":"2506.08121","title":"Continuous Policy and Value Iteration for Relaxed Stochastic Control Problems and Its Convergence","created":"2025-06-09","cited_by_count":1,"area":null},{"id":"2506.15954","title":"One Period to Rule Them All: Identifying Critical Learning Periods in Deep Networks","created":"2025-06-19","cited_by_count":1,"area":null},{"id":"2102.04613","title":"A New Framework for Variance-Reduced Hamiltonian Monte Carlo","created":"2021-02-09","cited_by_count":0,"area":null},{"id":"2310.09335","title":"The surrogate Gibbs-posterior of a corrected stochastic MALA: Towards uncertainty quantification for neural networks","created":"2023-10-13","cited_by_count":0,"area":null},{"id":"2407.02010","title":"Feynman-Kac Operator Expectation Estimator","created":"2024-07-02","cited_by_count":0,"area":null},{"id":"2501.17323","title":"Exploring Non-Convex Discrete Energy Landscapes: An Efficient Langevin-Like Sampler with Replica Exchange","created":"2025-01-28","cited_by_count":0,"area":null},{"id":"2503.02983","title":"BLADE: Bayesian Langevin Active Discovery with Replica Exchange for Identification of Complex Systems","created":"2025-03-04","cited_by_count":0,"area":null},{"id":"2510.02174","title":"Flatness-Aware Stochastic Gradient Langevin Dynamics","created":"2025-10-02","cited_by_count":0,"area":null},{"id":"2609.09473","title":"Mode Coverage in Normalizing Flow Boltzmann Generators via Log-Ratio Variation","created":"2026-09-08","cited_by_count":0,"area":null}],"next_cursor":null}