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Bayesian & Probabilistic

4,335 papers (2 classified directly here)

Subtopics

Probabilistic Modeling (2,599) Bayesian Learning (1,663) Bayesian Inference (523) Variational Inference (107) Gaussian Processes (6) Bayesian Networks (5)

Papers per year

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Papers (including subtopics)

Neural Diffusion Processes ICML 2023
Flat Seeking Bayesian Neural Networks NIPS 2023
Learning Robust Statistics for Simulation-based Inference under Model Misspecification NIPS 2023
Feature-Space Bayesian Adversarial Learning Improved Malware Detector Robustness AAAI 2023
Compositional Score Modeling for Simulation-Based Inference ICML 2023
Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation AISTATS 2023
Attention as Implicit Structural Inference NIPS 2023
Probabilistic Debiasing of Scene Graphs CVPR 2023
Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees JMLR 2023
Delving Into Discrete Normalizing Flows on SO(3) Manifold for Probabilistic Rotation Modeling CVPR 2023
Revisiting Logistic-softmax Likelihood in Bayesian Meta-Learning for Few-Shot Classification NIPS 2023
Learning the Finer Things: Bayesian Structure Learning at the Instantiation Level AAAI 2023
TopWORDS-Poetry: Simultaneous Text Segmentation and Word Discovery for Classical Chinese Poetry via Bayesian Inference EMNLP 2023
Bayesian Spanning Tree: Estimating the Backbone of the Dependence Graph JMLR 2023
Learning Procedure-Aware Video Representation From Instructional Videos and Their Narrations CVPR 2023
Probabilistic Volumetric Fusion for Dense Monocular SLAM WACV 2023
Bayesian Progressive Deep Topic Model with Knowledge Informed Textual Data Coarsening Process ICML 2023
Kernel-Matrix Determinant Estimates from stopped Cholesky Decomposition JMLR 2023
Compositional Probabilistic and Causal Inference using Tractable Circuit Models AISTATS 2023
Prior Specification for Bayesian Matrix Factorization via Prior Predictive Matching JMLR 2023
A Tale of Two Latent Flows: Learning Latent Space Normalizing Flow with Short-Run Langevin Flow for Approximate Inference AAAI 2023
Generative Label Enhancement with Gaussian Mixture and Partial Ranking AAAI 2023
Learning Noisy OR Bayesian Networks with Max-Product Belief Propagation ICML 2023
Switching Autoregressive Low-rank Tensor Models NIPS 2023
Uncertainty Quantification over Graph with Conformalized Graph Neural Networks NIPS 2023