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Bayesian & Probabilistic

3,963 papers (2 classified directly here)

Subtopics

Probabilistic Modeling (2,252) Variational Inference (802) Gaussian Processes (570) Bayesian Learning (455) Bayesian Optimization (221) Markov Chain Monte Carlo (143) Nonparametric Bayesian (86) Bayesian Networks (81) Conditional Random Fields (5)

Papers per year

9
118
124
394
151
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Papers (including subtopics)

GeoPhy: Differentiable Phylogenetic Inference via Geometric Gradients of Tree Topologies NIPS 2023
RevUp: Revise and Update Information Bottleneck for Event Representation EACL 2023
Semi-Supervised Deep Regression with Uncertainty Consistency and Variational Model Ensembling via Bayesian Neural Networks AAAI 2023
Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation NIPS 2023
Unbiased Multilevel Monte Carlo Methods for Intractable Distributions: MLMC Meets MCMC JMLR 2023
Nonlinear Structural Equation Model Guided Gaussian Mixture Hierarchical Topic Modeling ACL 2023
A Multi-Task Gaussian Process Model for Inferring Time-Varying Treatment Effects in Panel Data AISTATS 2023
Construction of Hierarchical Neural Architecture Search Spaces based on Context-free Grammars NIPS 2023
Interpreting Sentiment Composition with Latent Semantic Tree ACL 2023
ScanDMM: A Deep Markov Model of Scanpath Prediction for 360deg Images CVPR 2023
Preferential Subsampling for Stochastic Gradient Langevin Dynamics AISTATS 2023
Distilling knowledge from Gaussian process teacher to neural network student INTERSPEECH 2023
Learning-augmented count-min sketches via Bayesian nonparametrics JMLR 2023
Adaptive Cholesky Gaussian Processes AISTATS 2023
Bayesian online change point detection with Hilbert space approximate Student-t process ICML 2023
Efficient and Accurate Learning of Mixtures of Plackett-Luce Models AAAI 2023
Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models ICML 2023
Expressive probabilistic sampling in recurrent neural networks NIPS 2023
Causal Conditional Hidden Markov Model for Multimodal Traffic Prediction AAAI 2023
Latent Constraints on Unsupervised Text-Graph Alignment with Information Asymmetry AAAI 2023
Bayesian Federated Learning: A Survey IJCAI 2023
Posterior Consistency for Bayesian Relevance Vector Machines JMLR 2023
CataBEEM: Integrating Latent Interaction Categories in Node-wise Community Detection Models for Network Data ICML 2023
On Calibrating Diffusion Probabilistic Models NIPS 2023
Top Two Algorithms Revisited NIPS 2022