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)

Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs NIPS 2020
Quantile Graphical Models: a Bayesian Approach JMLR 2020
Discriminative Non-Parametric Learning of Arithmetic Circuits PGM 2020
Improving Local Identifiability in Probabilistic Box Embeddings NIPS 2020
Learning Joint Nonlinear Effects from Single-variable Interventions in the Presence of Hidden Confounders UAI 2020
Identifiability and Consistent Estimation of Nonparametric Translation Hidden Markov Models with General State Space JMLR 2020
Variational Pathway Reasoning for EEG Emotion Recognition AAAI 2020
Hawkesian Graphical Event Models PGM 2020
Faster Differentially Private Samplers via Rényi Divergence Analysis of Discretized Langevin MCMC NIPS 2020
Stochastic Deep Gaussian Processes over Graphs NIPS 2020
Non-reversible Gaussian processes for identifying latent dynamical structure in neural data NIPS 2020
Capsule Routing via Variational Bayes AAAI 2020
Probabilistic Orientation Estimation with Matrix Fisher Distributions NIPS 2020
On Infinite-Width Hypernetworks NIPS 2020
Structured Probabilistic End-to-End Learning from Crowds IJCAI 2020
Probabilistic Structural Latent Representation for Unsupervised Embedding CVPR 2020
Fast and Flexible Temporal Point Processes with Triangular Maps NIPS 2020
Source Separation with Deep Generative Priors ICML 2020
GP-VAE: Deep Probabilistic Time Series Imputation AISTATS 2020
Weakly Supervised Sequence Tagging from Noisy Rules AAAI 2020
The Hawkes Edge Partition Model for Continuous-time Event-based Temporal Networks UAI 2020
From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models ICML 2020
Federated Latent Dirichlet Allocation: A Local Differential Privacy Based Framework AAAI 2020
A Rule for Gradient Estimator Selection, with an Application to Variational Inference AISTATS 2020
Matérn Gaussian Processes on Riemannian Manifolds NIPS 2020