← Optimization & Theory
Machine Learning › Optimization & Theory ›

Bayesian Inference

4821 directly classified papers

Papers per year

Papers

NAS-X: Neural Adaptive Smoothing via Twisting NIPS 2023
BayesDAG: Gradient-Based Posterior Inference for Causal Discovery NIPS 2023
CBD: A Certified Backdoor Detector Based on Local Dominant Probability NIPS 2023
Prototype-based Aleatoric Uncertainty Quantification for Cross-modal Retrieval NIPS 2023
Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler's Rotation Equation NIPS 2023
Robust Gaussian process regression with the trimmed marginal likelihood UAI 2023
Knowledge Intensive Learning of Cutset Networks UAI 2023
Two-stage Kernel Bayesian Optimization in High Dimensions UAI 2023
Implicit Variational Inference for High-Dimensional Posteriors NIPS 2023
Particle-based Variational Inference with Generalized Wasserstein Gradient Flow NIPS 2023
BayesTune: Bayesian Sparse Deep Model Fine-tuning NIPS 2023
Sub-optimality of the Naive Mean Field approximation for proportional high-dimensional Linear Regression NIPS 2023
Probabilistic Weight Fixing: Large-scale training of neural network weight uncertainties for quantisation. NIPS 2023
L-C2ST: Local Diagnostics for Posterior Approximations in Simulation-Based Inference NIPS 2023
Improvements on Uncertainty Quantification for Node Classification via Distance Based Regularization NIPS 2023
Effective Bayesian Heteroscedastic Regression with Deep Neural Networks NIPS 2023
Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation NIPS 2023
Hierarchical Semi-Implicit Variational Inference with Application to Diffusion Model Acceleration NIPS 2023
Advancing Bayesian Optimization via Learning Correlated Latent Space NIPS 2023
Nonparametric Identifiability of Causal Representations from Unknown Interventions NIPS 2023
PAC-Bayes Generalization Certificates for Learned Inductive Conformal Prediction NIPS 2023
Hierarchical VAEs provide a normative account of motion processing in the primate brain NIPS 2023
VaRT: Variational Regression Trees NIPS 2023
On the Convergence of Black-Box Variational Inference NIPS 2023
MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under nonparametrized geometrical variability NIPS 2023