conftrace_
← Machine Learning
Machine Learning ›

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
'05
'10
'15
'20
'25

Papers (including subtopics)

Context-Aware Online Collective Inference for Templated Graphical Models ICML 2021
Kernel Stein Discrepancy Descent ICML 2021
Neural Temporal Point Processes: A Review IJCAI 2021
Non-approximate Inference for Collective Graphical Models on Path Graphs via Discrete Difference of Convex Algorithm NIPS 2021
Composing Normalizing Flows for Inverse Problems ICML 2021
Equivariant Learning of Stochastic Fields: Gaussian Processes and Steerable Conditional Neural Processes ICML 2021
Asymptotic Normality, Concentration, and Coverage of Generalized Posteriors JMLR 2021
Evaluating the Implicit Midpoint Integrator for Riemannian Hamiltonian Monte Carlo ICML 2021
Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL NIPS 2021
Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification EMNLP 2021
Combinatorial Gaussian Process Bandits with Probabilistically Triggered Arms AISTATS 2021
Prediction by Anticipation: An Action-Conditional Prediction Method Based on Interaction Learning ICCV 2021
A New Representation of Successor Features for Transfer across Dissimilar Environments ICML 2021
Exploiting Chain Rule and Bayes' Theorem to Compare Probability Distributions NIPS 2021
Exact Privacy Guarantees for Markov Chain Implementations of the Exponential Mechanism with Artificial Atoms NIPS 2021
HiABP: Hierarchical Initialized ABP for Unsupervised Representation Learning AAAI 2021
Moreau-Yosida $f$-divergences ICML 2021
Uncertain-aware Safe Exploratory Planning using Gaussian Process and Neural Control Contraction Metric L4DC 2021
Deconditional Downscaling with Gaussian Processes NIPS 2021
Lenient Regret and Good-Action Identification in Gaussian Process Bandits ICML 2021
Probabilistic Tensor Decomposition of Neural Population Spiking Activity NIPS 2021
Explaining A Black-box By Using A Deep Variational Information Bottleneck Approach AAAI 2021
Automatic variational inference with cascading flows ICML 2021
Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation ICML 2021
Uncertainty-Aware Multi-View Representation Learning AAAI 2021