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← Optimization & Theory
Machine Learning
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Optimization & Theory
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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
Stein Self-Repulsive Dynamics: Benefits From Past Samples
NIPS 2020
Generalised Bayesian Filtering via Sequential Monte Carlo
NIPS 2020
Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee
NIPS 2020
Deep Relational Topic Modeling via Graph Poisson Gamma Belief Network
NIPS 2020
Bayesian Deep Ensembles via the Neural Tangent Kernel
NIPS 2020
Model Selection for Production System via Automated Online Experiments
NIPS 2020
Ensembling geophysical models with Bayesian Neural Networks
NIPS 2020
Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization
NIPS 2020
Deep Transformers with Latent Depth
NIPS 2020
Bridging the Gap between Sample-based and One-shot Neural Architecture Search with BONAS
NIPS 2020
SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence
NIPS 2020
Approximation Based Variance Reduction for Reparameterization Gradients
NIPS 2020
Modular Meta-Learning with Shrinkage
NIPS 2020
Bidirectional Convolutional Poisson Gamma Dynamical Systems
NIPS 2020
Variance reduction for Random Coordinate Descent-Langevin Monte Carlo
NIPS 2020
Sequential Bayesian Experimental Design with Variable Cost Structure
NIPS 2020
Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian Optimization
NIPS 2020
Liberty or Depth: Deep Bayesian Neural Nets Do Not Need Complex Weight Posterior Approximations
NIPS 2020
PAC-Bayes Learning Bounds for Sample-Dependent Priors
NIPS 2020
Variational Policy Gradient Method for Reinforcement Learning with General Utilities
NIPS 2020
Reverse-engineering recurrent neural network solutions to a hierarchical inference task for mice
NIPS 2020
Probabilistic Circuits for Variational Inference in Discrete Graphical Models
NIPS 2020
A Non-Asymptotic Analysis for Stein Variational Gradient Descent
NIPS 2020
Bayesian Deep Learning and a Probabilistic Perspective of Generalization
NIPS 2020
Decision-Making with Auto-Encoding Variational Bayes
NIPS 2020
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