ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1806.10317
  4. Cited By
Adversarial Distillation of Bayesian Neural Network Posteriors

Adversarial Distillation of Bayesian Neural Network Posteriors

27 June 2018
Kuan-Chieh Wang
Paul Vicol
James Lucas
Li Gu
Roger C. Grosse
R. Zemel
    UQCVGANAAMLBDL
ArXiv (abs)PDFHTML

Papers citing "Adversarial Distillation of Bayesian Neural Network Posteriors"

24 / 24 papers shown
Title
PViT: Prior-augmented Vision Transformer for Out-of-distribution Detection
PViT: Prior-augmented Vision Transformer for Out-of-distribution Detection
Tianhao Zhang
Zhixiang Chen
Lyudmila Mihaylova
317
0
0
27 Oct 2024
Hyp-UML: Hyperbolic Image Retrieval with Uncertainty-aware Metric
  Learning
Hyp-UML: Hyperbolic Image Retrieval with Uncertainty-aware Metric Learning
Shiyang Yan
Zongxuan Liu
Lin Xu
67
0
0
12 Oct 2023
Meta-Learning via Classifier(-free) Diffusion Guidance
Meta-Learning via Classifier(-free) Diffusion Guidance
Elvis Nava
Seijin Kobayashi
Yifei Yin
Robert K. Katzschmann
Benjamin Grewe
VLM
71
6
0
17 Oct 2022
Hyper-Representations as Generative Models: Sampling Unseen Neural
  Network Weights
Hyper-Representations as Generative Models: Sampling Unseen Neural Network Weights
Konstantin Schurholt
Boris Knyazev
Xavier Giró-i-Nieto
Damian Borth
130
42
0
29 Sep 2022
Low-Precision Stochastic Gradient Langevin Dynamics
Low-Precision Stochastic Gradient Langevin Dynamics
Ruqi Zhang
A. Wilson
Chris De Sa
BDL
58
14
0
20 Jun 2022
Dense Uncertainty Estimation
Dense Uncertainty Estimation
Jing Zhang
Yuchao Dai
Mochu Xiang
Deng-Ping Fan
Peyman Moghadam
Mingyi He
Christian J. Walder
Kaihao Zhang
Mehrtash Harandi
Nick Barnes
UQCVBDL
130
11
0
13 Oct 2021
Introspective Robot Perception using Smoothed Predictions from Bayesian
  Neural Networks
Introspective Robot Perception using Smoothed Predictions from Bayesian Neural Networks
Jianxiang Feng
M. Durner
Zoltán-Csaba Márton
Ferenc Bálint-Benczédi
Rudolph Triebel
UQCVBDL
81
11
0
27 Sep 2021
A Survey of Uncertainty in Deep Neural Networks
A Survey of Uncertainty in Deep Neural Networks
J. Gawlikowski
Cedrique Rovile Njieutcheu Tassi
Mohsin Ali
Jongseo Lee
Matthias Humt
...
R. Roscher
Muhammad Shahzad
Wen Yang
R. Bamler
Xiaoxiang Zhu
BDLUQCVOOD
242
1,168
0
07 Jul 2021
Adversarial Machine Learning for Cybersecurity and Computer Vision:
  Current Developments and Challenges
Adversarial Machine Learning for Cybersecurity and Computer Vision: Current Developments and Challenges
B. Xi
AAML
39
29
0
30 Jun 2021
Laplace Redux -- Effortless Bayesian Deep Learning
Laplace Redux -- Effortless Bayesian Deep Learning
Erik A. Daxberger
Agustinus Kristiadi
Alexander Immer
Runa Eschenhagen
Matthias Bauer
Philipp Hennig
BDLUQCV
232
315
0
28 Jun 2021
PID-GAN: A GAN Framework based on a Physics-informed Discriminator for
  Uncertainty Quantification with Physics
PID-GAN: A GAN Framework based on a Physics-informed Discriminator for Uncertainty Quantification with Physics
Arka Daw
M. Maruf
Anuj Karpatne
AI4CE
88
42
0
06 Jun 2021
Infinitely Deep Bayesian Neural Networks with Stochastic Differential
  Equations
Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations
Winnie Xu
Ricky T. Q. Chen
Xuechen Li
David Duvenaud
BDLUQCV
90
49
0
12 Feb 2021
Hands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Users
Hands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Users
Laurent Valentin Jospin
Wray Buntine
F. Boussaïd
Hamid Laga
Bennamoun
OODBDLUQCV
93
632
0
14 Jul 2020
URSABench: Comprehensive Benchmarking of Approximate Bayesian Inference
  Methods for Deep Neural Networks
URSABench: Comprehensive Benchmarking of Approximate Bayesian Inference Methods for Deep Neural Networks
Meet P. Vadera
Adam D. Cobb
B. Jalaeian
Benjamin M. Marlin
BDLUQCV
81
17
0
08 Jul 2020
Variational Hyper-Encoding Networks
Variational Hyper-Encoding Networks
Phuoc Nguyen
T. Tran
Sunil R. Gupta
Santu Rana
H. Dam
Svetha Venkatesh
BDLDRL
32
3
0
18 May 2020
Generalized Bayesian Posterior Expectation Distillation for Deep Neural
  Networks
Generalized Bayesian Posterior Expectation Distillation for Deep Neural Networks
Meet P. Vadera
B. Jalaeian
Benjamin M. Marlin
BDLFedMLUQCV
64
20
0
16 May 2020
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep
  Learning
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning
Arsenii Ashukha
Alexander Lyzhov
Dmitry Molchanov
Dmitry Vetrov
UQCVFedML
93
320
0
15 Feb 2020
Your Classifier is Secretly an Energy Based Model and You Should Treat
  it Like One
Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One
Will Grathwohl
Kuan-Chieh Wang
J. Jacobsen
David Duvenaud
Mohammad Norouzi
Kevin Swersky
VLM
106
547
0
06 Dec 2019
Implicit Posterior Variational Inference for Deep Gaussian Processes
Implicit Posterior Variational Inference for Deep Gaussian Processes
Haibin Yu
Yizhou Chen
Zhongxiang Dai
K. H. Low
Patrick Jaillet
82
43
0
26 Oct 2019
Assessing the Robustness of Bayesian Dark Knowledge to Posterior
  Uncertainty
Assessing the Robustness of Bayesian Dark Knowledge to Posterior Uncertainty
Meet P. Vadera
Benjamin M. Marlin
BDLUQCV
23
1
0
04 Jun 2019
Ensemble Model Patching: A Parameter-Efficient Variational Bayesian
  Neural Network
Ensemble Model Patching: A Parameter-Efficient Variational Bayesian Neural Network
Oscar Chang
Yuling Yao
David Williams-King
Hod Lipson
BDLUQCV
71
8
0
23 May 2019
HyperGAN: A Generative Model for Diverse, Performant Neural Networks
HyperGAN: A Generative Model for Diverse, Performant Neural Networks
Neale Ratzlaff
Fuxin Li
69
64
0
30 Jan 2019
Probability Functional Descent: A Unifying Perspective on GANs,
  Variational Inference, and Reinforcement Learning
Probability Functional Descent: A Unifying Perspective on GANs, Variational Inference, and Reinforcement Learning
Casey Chu
Jose H. Blanchet
Peter Glynn
GAN
73
26
0
30 Jan 2019
Inhibited Softmax for Uncertainty Estimation in Neural Networks
Inhibited Softmax for Uncertainty Estimation in Neural Networks
Marcin Mo.zejko
Mateusz Susik
Rafal Karczewski
UQCV
75
29
0
03 Oct 2018
1