{"total":82,"rows":[{"id":"2106.14806","title":"Laplace Redux -- Effortless Bayesian Deep Learning","created":"2021-06-28","cited_by_count":365,"area":null},{"id":"2308.13111","title":"Bayesian Low-rank Adaptation for Large Language Models","created":"2023-08-24","cited_by_count":115,"area":null},{"id":"2404.11599","title":"Variational Bayesian Last Layers","created":"2024-04-17","cited_by_count":69,"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":"2402.00809","title":"Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI","created":"2024-02-01","cited_by_count":62,"area":null},{"id":"2206.08900","title":"Adapting the Linearised Laplace Model Evidence for Modern Deep Learning","created":"2022-06-17","cited_by_count":29,"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":"2306.11589","title":"Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent","created":"2023-06-20","cited_by_count":27,"area":null},{"id":"2309.16314","title":"A Primer on Bayesian Neural Networks: Review and Debates","created":"2023-09-28","cited_by_count":27,"area":null},{"id":"2111.03577","title":"Mixtures of Laplace Approximations for Improved Post-Hoc Uncertainty in Deep Learning","created":"2021-11-05","cited_by_count":25,"area":null},{"id":"2111.01968","title":"A Survey on Epistemic (Model) Uncertainty in Supervised Learning: Recent Advances and Applications","created":"2021-11-03","cited_by_count":24,"area":null},{"id":"2210.12928","title":"GFlowOut: Dropout with Generative Flow Networks","created":"2022-10-24","cited_by_count":22,"area":null},{"id":"2107.03955","title":"On Margins and Derandomisation in PAC-Bayes","created":"2021-07-08","cited_by_count":19,"area":null},{"id":"2110.03360","title":"Sparse MoEs meet Efficient Ensembles","created":"2021-10-07","cited_by_count":19,"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":"2302.12565","title":"Variational Linearized Laplace Approximation for Bayesian Deep Learning","created":"2023-02-24","cited_by_count":18,"area":null},{"id":"2406.03334","title":"Reparameterization invariance in approximate Bayesian inference","created":"2024-06-05","cited_by_count":17,"area":null},{"id":"2112.00195","title":"Efficient Online Bayesian Inference for Neural Bandits","created":"2021-12-01","cited_by_count":15,"area":null},{"id":"2305.16905","title":"Improving Neural Additive Models with Bayesian Principles","created":"2023-05-26","cited_by_count":15,"area":null},{"id":"2306.07158","title":"Riemannian Laplace approximations for Bayesian neural networks","created":"2023-06-12","cited_by_count":15,"area":null},{"id":"2312.15297","title":"Make Me a BNN: A Simple Strategy for Estimating Bayesian Uncertainty from Pre-trained Models","created":"2023-12-23","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":"2205.13340","title":"Deep Active Learning with Noise Stability","created":"2022-05-26","cited_by_count":14,"area":null},{"id":"2110.04020","title":"Pathologies in priors and inference for Bayesian transformers","created":"2021-10-08","cited_by_count":13,"area":null},{"id":"2406.05072","title":"Linearization Turns Neural Operators into Function-Valued Gaussian Processes","created":"2024-06-07","cited_by_count":12,"area":null},{"id":"2403.16732","title":"Enabling Uncertainty Estimation in Iterative Neural Networks","created":"2024-03-25","cited_by_count":11,"area":null},{"id":"2203.00479","title":"Uncertainty Estimation for Computed Tomography with a Linearised Deep Image Prior","created":"2022-02-28","cited_by_count":10,"area":null},{"id":"2302.08883","title":"Approximately Bayes-Optimal Pseudo Label Selection","created":"2023-02-17","cited_by_count":10,"area":null},{"id":"2404.10124","title":"Epistemic Uncertainty Quantification For Pre-trained Neural Network","created":"2024-04-15","cited_by_count":10,"area":null},{"id":"2206.07673","title":"Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling","created":"2022-06-15","cited_by_count":9,"area":null},{"id":"2207.05714","title":"Bayesian Experimental Design for Computed Tomography with the Linearised Deep Image Prior","created":"2022-07-11","cited_by_count":7,"area":null},{"id":"2209.15208","title":"Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel","created":"2022-09-30","cited_by_count":7,"area":null},{"id":"2302.06544","title":"Probabilistic Circuits That Know What They Don't Know","created":"2023-02-13","cited_by_count":7,"area":null},{"id":"2402.03495","title":"Partially Stochastic Infinitely Deep Bayesian Neural Networks","created":"2024-02-05","cited_by_count":6,"area":null},{"id":"2310.06643","title":"Implicit Variational Inference for High-Dimensional Posteriors","created":"2023-10-10","cited_by_count":5,"area":null},{"id":"2410.23910","title":"Uncertainty Estimation for 3D Object Detection via Evidential Learning","created":"2024-10-31","cited_by_count":5,"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":"2107.02572","title":"Unsupervised Knowledge-Transfer for Learned Image Reconstruction","created":"2021-07-06","cited_by_count":4,"area":null},{"id":"2306.01452","title":"dugMatting: Decomposed-Uncertainty-Guided Matting","created":"2023-06-02","cited_by_count":4,"area":null},{"id":"2310.19608","title":"On Feynman--Kac training of partial Bayesian neural networks","created":"2023-10-30","cited_by_count":4,"area":null},{"id":"2404.15657","title":"FedSI: Federated Subnetwork Inference for Efficient Uncertainty Quantification","created":"2024-04-24","cited_by_count":4,"area":null},{"id":"2502.11617","title":"In-Context Parametric Inference: Point or Distribution Estimators?","created":"2025-02-17","cited_by_count":4,"area":null},{"id":"2404.01801","title":"EventSleep: Sleep Activity Recognition with Event Cameras","created":"2024-04-02","cited_by_count":3,"area":null},{"id":"2410.16901","title":"Bayes without Underfitting: Fully Correlated Deep Learning Posteriors via Alternating Projections","created":"2024-10-22","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":"2210.12957","title":"On the optimization and pruning for Bayesian deep learning","created":"2022-10-24","cited_by_count":2,"area":null},{"id":"2407.07372","title":"Multi-modal MRI Translation via Evidential Regression and Distribution Calibration","created":"2024-07-10","cited_by_count":2,"area":null},{"id":"2412.04177","title":"Fixed-Mean Gaussian Processes for Post-hoc Bayesian Deep Learning","created":"2024-12-05","cited_by_count":2,"area":null},{"id":"2502.02345","title":"Low Rank Based Subspace Inference for the Laplace Approximation of Bayesian Neural Networks","created":"2025-02-04","cited_by_count":2,"area":null},{"id":"2506.19144","title":"Posterior Contraction for Sparse Neural Networks in Besov Spaces with Intrinsic Dimensionality","created":"2025-06-23","cited_by_count":2,"area":null},{"id":"2512.01384","title":"CLAPS: Aleatoric-Epistemic Scaling via Last-Layer Laplace for Conformal Regression","created":"2025-12-01","cited_by_count":2,"area":null},{"id":"2302.10279","title":"Image Reconstruction via Deep Image Prior Subspaces","created":"2023-02-20","cited_by_count":1,"area":null},{"id":"2308.06129","title":"Uncertainty Quantification for Image-based Traffic Prediction across Cities","created":"2023-08-11","cited_by_count":1,"area":null},{"id":"2405.17277","title":"Gradients of Functions of Large Matrices","created":"2024-05-27","cited_by_count":1,"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":"2408.14325","title":"Function-Space MCMC for Bayesian Wide Neural Networks","created":"2024-08-26","cited_by_count":1,"area":null},{"id":"2410.22948","title":"ELBOing Stein: Variational Bayes with Stein Mixture Inference","created":"2024-10-30","cited_by_count":1,"area":null},{"id":"2411.04397","title":"A Bayesian Mixture Model of Temporal Point Processes with Determinantal Point Process Prior","created":"2024-11-07","cited_by_count":1,"area":null},{"id":"2507.14652","title":"Accelerating Hamiltonian Monte Carlo for Bayesian Inference in Neural Networks and Neural Operators","created":"2025-07-19","cited_by_count":1,"area":null},{"id":"2507.20272","title":"Approximating Full Conformal Prediction for Neural Network Regression with Gauss-Newton Influence","created":"2025-07-27","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":"2603.29466","title":"An Isotropic Approach to Efficient Uncertainty Quantification with Gradient Norms","created":"2026-03-31","cited_by_count":1,"area":null},{"id":"2605.21765","title":"Position: The Time for Sampling Is Now! Charting a New Course for Bayesian Deep Learning","created":"2026-05-20","cited_by_count":1,"area":null},{"id":"2202.04392","title":"Model Architecture Adaption for Bayesian Neural Networks","created":"2022-02-09","cited_by_count":0,"area":null},{"id":"2307.06055","title":"Function-Space Regularization for Deep Bayesian Classification","created":"2023-07-12","cited_by_count":0,"area":null},{"id":"2307.06424","title":"Robust scalable initialization for Bayesian variational inference with multi-modal Laplace approximations","created":"2023-07-12","cited_by_count":0,"area":null},{"id":"2309.04742","title":"Affine Invariant Ensemble Transform Methods to Improve Predictive Uncertainty in Neural Networks","created":"2023-09-09","cited_by_count":0,"area":null},{"id":"2405.17666","title":"Structured Partial Stochasticity in Bayesian Neural Networks","created":"2024-05-27","cited_by_count":0,"area":null},{"id":"2411.01887","title":"Stein Variational Newton Neural Network Ensembles","created":"2024-11-04","cited_by_count":0,"area":null},{"id":"2505.02590","title":"Ensemble Kalman filter for uncertainty in human language comprehension","created":"2025-05-05","cited_by_count":0,"area":null},{"id":"2505.20235","title":"Variational Deep Learning via Implicit Regularization","created":"2025-05-26","cited_by_count":0,"area":null},{"id":"2508.11961","title":"PEdger++: Practical Edge Detection via Assembling Cross Information","created":"2025-08-16","cited_by_count":0,"area":null},{"id":"2511.01628","title":"Partial Trace-Class Bayesian Neural Networks","created":"2025-11-03","cited_by_count":0,"area":null},{"id":"2605.01632","title":"Perturb and Correct: Post-Hoc Ensembles using Affine Redundancy","created":"2026-05-02","cited_by_count":0,"area":null},{"id":"2605.07706","title":"Bayesian Fine-tuning in Projected Subspaces","created":"2026-05-08","cited_by_count":0,"area":null},{"id":"2605.09075","title":"Optimality of Sub-network Laplace Approximations: New Results and Methods","created":"2026-05-09","cited_by_count":0,"area":null},{"id":"2605.12208","title":"Self-Supervised Laplace Approximation for Bayesian Uncertainty Quantification","created":"2026-05-12","cited_by_count":0,"area":null},{"id":"2607.23860","title":"Controllable Diversity in Normalization-Based Implicit Ensembles via Softmax-Temperature Modulation","created":"2026-07-26","cited_by_count":0,"area":null},{"id":"2608.07183","title":"Conformal Fusion Under Missing Modalities","created":"2026-08-07","cited_by_count":0,"area":null},{"id":"2610.14875","title":"Contrastive Linearized Laplace: Loss Geometry, Valid Repairs, and Reliable Cores","created":"2026-10-10","cited_by_count":0,"area":null},{"id":"2610.17146","title":"SCOPE Before You Sample: Conformal Scores Guide Posterior Exploration for Fast and Calibrated Bayesian Predictive Inference","created":"2026-10-12","cited_by_count":0,"area":null}],"next_cursor":null}