Bayesian & Probabilistic

A probabilistic framework for task-aligned intra- and inter-area neural manifold estimation ICLR 2023 A Probabilistic Graph Diffusion Model for Source Localization (Student Abstract) AAAI 2023 A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness JMLR 2023 ASTRA: Understanding the practical impact of robustness for probabilistic programs UAI 2023 Asymptotic Bayes risk of semi-supervised multitask learning on Gaussian mixture AISTATS 2023 Asymptotics of Bayesian Uncertainty Estimation in Random Features Regression NeurIPS 2023 A Tale of Two Latent Flows: Learning Latent Space Normalizing Flow with Short-Run Langevin Flow for Approximate Inference AAAI 2023 A Theoretical Framework for Inference and Learning in Predictive Coding Networks ICLR 2023 Attention as Implicit Structural Inference NeurIPS 2023 A Unifying Formal Approach to Importance Values in Boolean Functions IJCAI 2023 Autonomous Navigation, Mapping and Exploration with Gaussian Processes RSS 2023 Autoregressive Conditional Neural Processes ICLR 2023 BaCaDI: Bayesian Causal Discovery with Unknown Interventions AISTATS 2023 Balancing Risk and Reward: A Batched-Bandit Strategy for Automated Phased Release NeurIPS 2023 BANSAC: A Dynamic BAyesian Network for Adaptive SAmple Consensus ICCV 2023 Batch Bayesian Optimization For Replicable Experimental Design NeurIPS 2023 Bayesian Active Causal Discovery with Multi-Fidelity Experiments NeurIPS 2023 Bayesian Convolutional Deep Sets with Task-Dependent Stationary Prior AISTATS 2023 Bayesian Cross-Modal Alignment Learning for Few-Shot Out-of-Distribution Generalization AAAI 2023 Bayesian Design Principles for Frequentist Sequential Learning ICML 2023 Bayesian Estimation of Differential Privacy ICML 2023 Bayesian Federated Learning: A Survey IJCAI 2023 Bayesian Hierarchical Models for Counterfactual Estimation AISTATS 2023 Bayesian inference for vertex-series-parallel partial orders UAI 2023 Bayesian Learning via Q-Exponential Process NeurIPS 2023