conftrace
_
Papers
Trends
Conferences
Explore
Authors
Papers
Trends
Conferences
Explore
Authors
Topics
Keywords
Achievements
← Optimization & Theory
Machine Learning
›
Optimization & Theory
›
Bayesian Inference
4,821 papers
Papers per year
2001: 1
2002: 1
2003: 5
2004: 2
2005: 9
2006: 22
2007: 32
2008: 36
2009: 38
2010: 72
2011: 86
2012: 85
2013: 148
2014: 179
2015: 162
2016: 183
2017: 255
2018: 278
2019: 458
2020: 469
2021: 554
2022: 477
2023: 576
2024: 348
2025: 255
2026: 90
Papers
Expert-Supervised Reinforcement Learning for Offline Policy Learning and Evaluation
NIPS 2020
BayReL: Bayesian Relational Learning for Multi-omics Data Integration
NIPS 2020
Quantized Variational Inference
NIPS 2020
Asymptotically Optimal Exact Minibatch Metropolis-Hastings
NIPS 2020
Exponential ergodicity of mirror-Langevin diffusions
NIPS 2020
Flexible mean field variational inference using mixtures of non-overlapping exponential families
NIPS 2020
Gradient-EM Bayesian Meta-Learning
NIPS 2020
High-Dimensional Bayesian Optimization via Nested Riemannian Manifolds
NIPS 2020
Matrix Completion with Quantified Uncertainty through Low Rank Gaussian Copula
NIPS 2020
Uncertainty-aware Self-training for Few-shot Text Classification
NIPS 2020
BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization
NIPS 2020
Uncertainty-Aware Learning for Zero-Shot Semantic Segmentation
NIPS 2020
High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization
NIPS 2020
Fast Matrix Square Roots with Applications to Gaussian Processes and Bayesian Optimization
NIPS 2020
Scalable Belief Propagation via Relaxed Scheduling
NIPS 2020
Matrix Inference and Estimation in Multi-Layer Models
NIPS 2020
Variational Interaction Information Maximization for Cross-domain Disentanglement
NIPS 2020
Manifold GPLVMs for discovering non-Euclidean latent structure in neural data
NIPS 2020
Action-Conditional Recurrent Kalman Networks For Forward and Inverse Dynamics Learning
CORL 2020
STReSSD: Sim-To-Real from Sound for Stochastic Dynamics
CORL 2020
Incremental learning of EMG-based control commands using Gaussian Processes
CORL 2020
Stein Variational Model Predictive Control
CORL 2020
The Stanford Acuity Test: A Precise Vision Test Using Bayesian Techniques and a Discovery in Human Visual Response
AAAI 2020
TrueLearn: A Family of Bayesian Algorithms to Match Lifelong Learners to Open Educational Resources
AAAI 2020
Privacy-Preserving Gradient Boosting Decision Trees
AAAI 2020
<
1
…
96
97
98
…
193
>