Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
1601.00670
Cited By
v1
v2
v3
v4
v5
v6
v7
v8
v9 (latest)
Variational Inference: A Review for Statisticians
4 January 2016
David M. Blei
A. Kucukelbir
Jon D. McAuliffe
BDL
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Variational Inference: A Review for Statisticians"
50 / 1,838 papers shown
Title
Addressing the Inconsistency in Bayesian Deep Learning via Generalized Laplace Approximation
Yinsong Chen
Samson S. Yu
Zhong Li
Chee Peng Lim
BDL
80
0
0
01 Jul 2025
Bayesian Joint Model of Multi-Sensor and Failure Event Data for Multi-Mode Failure Prediction
Sina Aghaee Dabaghan Fard
Minhee Kim
Akash Deep
Jaesung Lee
7
0
0
20 Jun 2025
Variational Inference with Mixtures of Isotropic Gaussians
Marguerite Petit-Talamon
Marc Lambert
Anna Korba
BDL
49
0
0
16 Jun 2025
Bayesian Inverse Physics for Neuro-Symbolic Robot Learning
Octavio Arriaga
Rebecca Adam
Melvin Laux
L. Gutzeit
Marco Ragni
Jan Peters
Frank Kirchner
PINN
AI4CE
35
0
0
10 Jun 2025
Variational Inference Optimized Using the Curved Geometry of Coupled Free Energy
Kenric Nelson
Igor Oliveira
Amenah Al-Najafi
Fode Zhang
Hon Keung Tony Ng
DRL
41
0
0
10 Jun 2025
Stability of Mean-Field Variational Inference
Shunan Sheng
Bohan Wu
Alberto González-Sanz
Marcel Nutz
22
0
0
09 Jun 2025
Quantifying Adversarial Uncertainty in Evidential Deep Learning using Conflict Resolution
Charmaine Barker
Daniel Bethell
Simos Gerasimou
AAML
57
0
0
06 Jun 2025
Variational Inference for Quantum HyperNetworks
Luca Nepote
Alix Lhéritier
Nicolas Bondoux
Marios Kountouris
Maurizio Filippone
MQ
60
0
0
06 Jun 2025
RNE: a plug-and-play framework for diffusion density estimation and inference-time control
Jiajun He
Jose Miguel Hernandez-Lobato
Yuanqi Du
Francisco Vargas
98
0
0
06 Jun 2025
Sequential Monte Carlo approximations of Wasserstein--Fisher--Rao gradient flows
Francesca R. Crucinio
Sahani Pathiraja
60
0
0
06 Jun 2025
Exploring bidirectional bounds for minimax-training of Energy-based models
Cong Geng
Jia Wang
Li Chen
Zhiyong Gao
J. Frellsen
Søren Hauberg
102
0
0
05 Jun 2025
Amortized variational transdimensional inference
Laurence Davies
Dan Mackinlay
Rafael Oliveira
Scott A. Sisson
DRL
BDL
123
0
0
05 Jun 2025
Self-supervised Latent Space Optimization with Nebula Variational Coding
Yida Wang
D. Tan
Nassir Navab
Federico Tombari
DRL
SSL
81
1
0
02 Jun 2025
Asymptotically exact variational flows via involutive MCMC kernels
Zuheng Xu
Trevor Campbell
36
0
0
02 Jun 2025
Constrained Stein Variational Gradient Descent for Robot Perception, Planning, and Identification
Griffin Tabor
Tucker Hermans
32
0
0
31 May 2025
Normalizing Flows are Capable Models for RL
Raj Ghugare
Benjamin Eysenbach
OffRL
AI4CE
86
0
0
29 May 2025
Why Machine Learning Models Fail to Fully Capture Epistemic Uncertainty
Sebastián Jiménez
Mira Jürgens
Willem Waegeman
UD
PER
61
0
0
29 May 2025
STACI: Spatio-Temporal Aleatoric Conformal Inference
Brandon Feng
David K. Park
Xihaier Luo
Arantxa Urdangarin
Shinjae Yoo
Brian J. Reich
29
0
0
27 May 2025
Semi-supervised Clustering Through Representation Learning of Large-scale EHR Data
Linshanshan Wang
Mengyan Li
Zongqi Xia
Molei Liu
Tianxi Cai
22
0
0
27 May 2025
Unfolding AlphaFold's Bayesian Roots in Probability Kinematics
T. Hamelryck
K. Mardia
AI4CE
21
0
0
26 May 2025
An Iterative Framework for Generative Backmapping of Coarse Grained Proteins
Georgios Kementzidis
Erin Wong
John Nicholson
Ruichen Xu
Yuefan Deng
53
0
0
23 May 2025
Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems
Jiayi Geng
Howard Chen
Dilip Arumugam
Thomas L. Griffiths
109
0
0
23 May 2025
Sequential Monte Carlo for Policy Optimization in Continuous POMDPs
Hany Abdulsamad
Sahel Iqbal
Simo Särkkä
72
0
0
22 May 2025
Last Layer Empirical Bayes
Valentin Villecroze
Yixin Wang
Gabriel Loaiza-Ganem
UQCV
BDL
71
0
0
21 May 2025
Sample and Computationally Efficient Continuous-Time Reinforcement Learning with General Function Approximation
Runze Zhao
Yue Yu
Adams Yiyue Zhu
Chen Yang
Dongruo Zhou
48
0
0
20 May 2025
Personalized Bayesian Federated Learning with Wasserstein Barycenter Aggregation
Ting Wei
Biao Mei
Junliang Lyu
Renquan Zhang
Feng Zhou
Yifan Sun
FedML
75
0
0
20 May 2025
STRIDE: Sparse Techniques for Regression in Deep Gaussian Processes
Simon Urbainczyk
Aretha L. Teckentrup
Jonas Latz
GP
123
0
0
16 May 2025
Identifying Causal Direction via Variational Bayesian Compression
Quang-Duy Tran
Bao Duong
Phuoc Nguyen
Thin Nguyen
CML
121
0
0
12 May 2025
Combining Bayesian Inference and Reinforcement Learning for Agent Decision Making: A Review
Chengmin Zhou
Ville Kyrki
Pasi Fränti
Laura Ruotsalainen
BDL
AI4CE
121
0
0
12 May 2025
Boosting Statistic Learning with Synthetic Data from Pretrained Large Models
Jialong Jiang
Wenkang Hu
Jian Huang
Yuling Jiao
Xu Liu
DiffM
83
0
0
08 May 2025
Taming OOD Actions for Offline Reinforcement Learning: An Advantage-Based Approach
Xuyang Chen
Keyu Yan
Lin Zhao
OffRL
119
1
0
08 May 2025
Latent Adaptive Planner for Dynamic Manipulation
Donghun Noh
Deqian Kong
Minglu Zhao
Andrew Lizarraga
Jianwen Xie
Ying Nian Wu
Dennis W. Hong
407
1
0
06 May 2025
Variational Formulation of the Particle Flow Particle Filter
Yinzhuang Yi
Jorge Cortés
Nikolay Atanasov
75
0
0
06 May 2025
Bayesian Robust Aggregation for Federated Learning
Aleksandr Karakulev
Usama Zafar
Salman Toor
Prashant Singh
FedML
99
0
0
05 May 2025
Evolution of Gaussians in the Hellinger-Kantorovich-Boltzmann gradient flow
Matthias Liero
Alexander Mielke
Oliver Tse
Jia Jie Zhu
89
1
0
29 Apr 2025
Bayesian Optimization-based Tire Parameter and Uncertainty Estimation for Real-World Data
Sven Goblirsch
Benedikt Ruhland
Johannes Betz
Markus Lienkamp
76
0
0
29 Apr 2025
Factor Analysis with Correlated Topic Model for Multi-Modal Data
Małgorzata Łazęcka
Ewa Szczurek
48
0
0
26 Apr 2025
Segmentation with Noisy Labels via Spatially Correlated Distributions
Ryu Tadokoro
Tsukasa Takagi
Shin-ichi Maeda
63
0
0
21 Apr 2025
Uncertainty quantification of neural network models of evolving processes via Langevin sampling
Cosmin Safta
Reese E. Jones
Ravi G. Patel
Raelynn Wonnacot
Dan S. Bolintineanu
Craig M. Hamel
S. Kramer
BDL
126
0
0
21 Apr 2025
Variational Autoencoder Framework for Hyperspectral Retrievals (Hyper-VAE) of Phytoplankton Absorption and Chlorophyll a in Coastal Waters for NASA's EMIT and PACE Missions
Jiadong Lou
Bingqing Liu
Yuanheng Xiong
Xiaodong Zhang
Xu Yuan
56
2
0
18 Apr 2025
An Image is Worth
K
K
K
Topics: A Visual Structural Topic Model with Pretrained Image Embeddings
Matías Piqueras
Alexandra Segerberg
Matteo Magnani
Måns Magnusson
Nataša Sladoje
106
0
0
14 Apr 2025
Ensemble-Enhanced Graph Autoencoder with GAT and Transformer-Based Encoders for Robust Fault Diagnosis
Moirangthem Tiken Singh
AI4CE
62
1
0
13 Apr 2025
Stacking Variational Bayesian Monte Carlo
Francesco Silvestrin
Chengkun Li
Luigi Acerbi
BDL
104
0
0
07 Apr 2025
PRISM: Probabilistic Representation for Integrated Shape Modeling and Generation
Lei Cheng
Mahdi Saleh
Qing Cheng
Lu Sang
Hongli Xu
Zorah Lähner
F. Tombari
48
0
0
06 Apr 2025
Variational Self-Supervised Learning
Mehmet Can Yavuz
Berrin Yanikoglu
SSL
178
0
0
06 Apr 2025
Taming High-Dimensional Dynamics: Learning Optimal Projections onto Spectral Submanifolds
Hugo Buurmeijer
Luis A. Pabon
J. I. Alora
Roshan S. Kaundinya
George Haller
Marco Pavone
116
0
0
04 Apr 2025
Stochastic Variational Inference with Tuneable Stochastic Annealing
John Paisley
G. Fazelnia
Brian Barr
53
0
0
04 Apr 2025
Sparse Gaussian Neural Processes
Tommy Rochussen
Vincent Fortuin
BDL
UQCV
198
0
0
02 Apr 2025
Probabilistic Curriculum Learning for Goal-Based Reinforcement Learning
Llewyn Salt
Marcus Gallagher
64
1
0
02 Apr 2025
Multi-fidelity Parameter Estimation Using Conditional Diffusion Models
Caroline Tatsuoka
Minglei Yang
Dongbin Xiu
Guannan Zhang
DiffM
117
2
0
02 Apr 2025
1
2
3
4
...
35
36
37
Next