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Learnable Bernoulli Dropout for Bayesian Deep Learning

Learnable Bernoulli Dropout for Bayesian Deep Learning

International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
12 February 2020
Shahin Boluki
Randy Ardywibowo
Siamak Zamani Dadaneh
Mingyuan Zhou
Xiaoning Qian
    BDL
ArXiv (abs)PDFHTML

Papers citing "Learnable Bernoulli Dropout for Bayesian Deep Learning"

20 / 20 papers shown
Motif Guided Graph Transformer with Combinatorial Skeleton Prototype Learning for Skeleton-Based Person Re-Identification
Motif Guided Graph Transformer with Combinatorial Skeleton Prototype Learning for Skeleton-Based Person Re-Identification
Haocong Rao
Chunyan Miao
499
1
0
12 Dec 2024
Diffusion Boosted Trees
Diffusion Boosted Trees
Xizewen Han
Mingyuan Zhou
AI4CE
439
1
0
03 Jun 2024
On the Temperature of Bayesian Graph Neural Networks for Conformal
  Prediction
On the Temperature of Bayesian Graph Neural Networks for Conformal Prediction
Seohyeon Cha
Honggu Kang
Joonhyuk Kang
557
4
0
17 Oct 2023
Gated Compression Layers for Efficient Always-On Models
Gated Compression Layers for Efficient Always-On Models
Haiguang Li
T. Thormundsson
I. Poupyrev
N. Gillian
253
3
0
15 Mar 2023
GFlowOut: Dropout with Generative Flow Networks
GFlowOut: Dropout with Generative Flow NetworksInternational Conference on Machine Learning (ICML), 2022
Dianbo Liu
Moksh Jain
Bonaventure F. P. Dossou
Qianli Shen
Salem Lahlou
...
Dinghuai Zhang
N. Hassen
Xu Ji
Kenji Kawaguchi
Yoshua Bengio
UQCVBDLOOD
325
27
0
24 Oct 2022
Gating Dropout: Communication-efficient Regularization for Sparsely
  Activated Transformers
Gating Dropout: Communication-efficient Regularization for Sparsely Activated TransformersInternational Conference on Machine Learning (ICML), 2022
R. Liu
Young Jin Kim
Alexandre Muzio
Hany Awadalla
MoE
182
30
0
28 May 2022
Learnable Model Augmentation Self-Supervised Learning for Sequential
  Recommendation
Learnable Model Augmentation Self-Supervised Learning for Sequential Recommendation
Yongjing Hao
Pengpeng Zhao
Xuefeng Xian
Guanfeng Liu
Deqing Wang
Lei Zhao
Yanchi Liu
Victor S. Sheng
AI4TSLRMSSL
226
3
0
21 Apr 2022
VFDS: Variational Foresight Dynamic Selection in Bayesian Neural
  Networks for Efficient Human Activity Recognition
VFDS: Variational Foresight Dynamic Selection in Bayesian Neural Networks for Efficient Human Activity RecognitionInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Randy Ardywibowo
Shahin Boluki
Zinan Lin
Bobak J. Mortazavi
Shuai Huang
Xiaoning Qian
193
2
0
31 Mar 2022
Gated Linear Model induced U-net for surrogate modeling and uncertainty
  quantification
Gated Linear Model induced U-net for surrogate modeling and uncertainty quantification
Sai Krishna Mendu
S. Chakraborty
BDLAI4CE
198
2
0
08 Nov 2021
Data-driven discovery of interpretable causal relations for deep
  learning material laws with uncertainty propagation
Data-driven discovery of interpretable causal relations for deep learning material laws with uncertainty propagationGranular Matter (GM), 2021
Xiao Sun
B. Bahmani
Nikolaos N. Vlassis
WaiChing Sun
Yanxun Xu
CMLAI4CE
256
32
0
20 May 2021
Not All Attention Is All You Need
Not All Attention Is All You Need
Hongqiu Wu
Hai Zhao
Min Zhang
382
11
0
10 Apr 2021
Contextual Dropout: An Efficient Sample-Dependent Dropout Module
Contextual Dropout: An Efficient Sample-Dependent Dropout ModuleInternational Conference on Learning Representations (ICLR), 2021
Xinjie Fan
Shujian Zhang
Korawat Tanwisuth
Xiaoning Qian
Mingyuan Zhou
OODBDLUQCV
222
32
0
06 Mar 2021
A Bayesian Neural Network based on Dropout Regulation
A Bayesian Neural Network based on Dropout Regulation
Claire Theobald
Frédéric Pennerath
Brieuc Conan-Guez
Miguel Couceiro
A. Napoli
BDL
120
4
0
03 Feb 2021
Notes on the Behavior of MC Dropout
Notes on the Behavior of MC Dropout
Francesco Verdoja
Ville Kyrki
UQCVOODBDL
330
42
0
06 Aug 2020
NADS: Neural Architecture Distribution Search for Uncertainty Awareness
NADS: Neural Architecture Distribution Search for Uncertainty AwarenessInternational Conference on Machine Learning (ICML), 2020
Randy Ardywibowo
Shahin Boluki
Xinyu Gong
Zinan Lin
Xiaoning Qian
UQCV
238
19
0
11 Jun 2020
Bayesian Graph Neural Networks with Adaptive Connection Sampling
Bayesian Graph Neural Networks with Adaptive Connection Sampling
Arman Hasanzadeh
Ehsan Hajiramezanali
Shahin Boluki
Mingyuan Zhou
N. Duffield
Krishna R. Narayanan
Xiaoning Qian
BDL
361
140
0
07 Jun 2020
Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and
  Self-Control Gradient Estimator
Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and Self-Control Gradient Estimator
Siamak Zamani Dadaneh
Shahin Boluki
Mingzhang Yin
Mingyuan Zhou
Xiaoning Qian
BDLDRL
124
24
0
21 May 2020
ARSM Gradient Estimator for Supervised Learning to Rank
ARSM Gradient Estimator for Supervised Learning to RankIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019
Siamak Zamani Dadaneh
Shahin Boluki
Mingyuan Zhou
Xiaoning Qian
202
9
0
01 Nov 2019
Semi-Implicit Stochastic Recurrent Neural Networks
Semi-Implicit Stochastic Recurrent Neural NetworksIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019
Ehsan Hajiramezanali
Arman Hasanzadeh
N. Duffield
Krishna R. Narayanan
Mingyuan Zhou
Xiaoning Qian
BDL
188
5
0
28 Oct 2019
DropConnect Is Effective in Modeling Uncertainty of Bayesian Deep
  Networks
DropConnect Is Effective in Modeling Uncertainty of Bayesian Deep NetworksScientific Reports (Sci Rep), 2019
Aryan Mobiny
H. Nguyen
S. Moulik
Naveen Garg
Carol C. Wu
UQCVBDL
219
193
0
07 Jun 2019
1
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