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1802.09127
Cited By
Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling
International Conference on Learning Representations (ICLR), 2018
26 February 2018
C. Riquelme
George Tucker
Jasper Snoek
BDL
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Papers citing
"Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling"
50 / 231 papers shown
Unbiased Decisions Reduce Regret: Adversarial Domain Adaptation for the Bank Loan Problem
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Shaun Singh
Aldo Pacchiano
Benjamin Walker
Terry Lyons
Jakob N. Foerster
FaML
197
0
0
15 Aug 2023
VITS : Variational Inference Thompson Sampling for contextual bandits
International Conference on Machine Learning (ICML), 2023
Pierre Clavier
Tom Huix
Alain Durmus
386
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19 Jul 2023
Density Uncertainty Layers for Reliable Uncertainty Estimation
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Yookoon Park
David M. Blei
UQCV
BDL
200
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21 Jun 2023
Collapsed Inference for Bayesian Deep Learning
Neural Information Processing Systems (NeurIPS), 2023
Zhe Zeng
Karen Ullrich
FedML
BDL
UQCV
362
11
0
16 Jun 2023
Langevin Thompson Sampling with Logarithmic Communication: Bandits and Reinforcement Learning
International Conference on Machine Learning (ICML), 2023
Amin Karbasi
Nikki Lijing Kuang
Yi-An Ma
Siddharth Mitra
OffRL
196
6
0
15 Jun 2023
Diffusion Models for Black-Box Optimization
International Conference on Machine Learning (ICML), 2023
S. Krishnamoorthy
Satvik Mashkaria
Aditya Grover
DiffM
378
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0
12 Jun 2023
Representation-Driven Reinforcement Learning
International Conference on Machine Learning (ICML), 2023
Ofir Nabati
Guy Tennenholtz
Shie Mannor
300
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0
31 May 2023
Deep Stochastic Processes via Functional Markov Transition Operators
Neural Information Processing Systems (NeurIPS), 2023
Jin Xu
Emilien Dupont
Kaspar Martens
Tom Rainforth
Yee Whye Teh
261
6
0
24 May 2023
Memory Efficient Neural Processes via Constant Memory Attention Block
International Conference on Machine Learning (ICML), 2023
Leo Feng
Frederick Tung
Hossein Hajimirsadeghi
Yoshua Bengio
Mohamed Osama Ahmed
318
8
0
23 May 2023
Learning Personalized Page Content Ranking Using Customer Representation
Xin Shen
Yan Zhao
Sujan Perera
Yujia Liu
Jinyun Yan
Mitchell Goodman
BDL
176
9
0
09 May 2023
Neural Exploitation and Exploration of Contextual Bandits
Yikun Ban
Yuchen Yan
A. Banerjee
Jingrui He
214
9
0
05 May 2023
Expertise Trees Resolve Knowledge Limitations in Collective Decision-Making
International Conference on Machine Learning (ICML), 2023
Axel Abels
Tom Lenaerts
V. Trianni
Ann Nowé
253
2
0
02 May 2023
Posterior Sampling for Deep Reinforcement Learning
International Conference on Machine Learning (ICML), 2023
Remo Sasso
Michelangelo Conserva
Paulo E. Rauber
OffRL
BDL
241
13
0
30 Apr 2023
Towards Reliable Uncertainty Quantification via Deep Ensembles in Multi-output Regression Task
Engineering applications of artificial intelligence (Eng. Appl. Artif. Intell.), 2023
Sunwoong Yang
K. Yee
UQCV
301
18
0
28 Mar 2023
Adaptive Endpointing with Deep Contextual Multi-armed Bandits
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2023
Do June Min
A. Stolcke
A. Raju
Colin Vaz
Di He
Venkatesh Ravichandran
V. Trinh
OffRL
142
1
0
23 Mar 2023
Energy Regularized RNNs for Solving Non-Stationary Bandit Problems
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2023
Michael Rotman
Lior Wolf
132
1
0
12 Mar 2023
Variational Boosted Soft Trees
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Tristan Cinquin
Tammo Rukat
Philipp Schmidt
Martin Wistuba
Artur Bekasov
BDL
UQCV
248
0
0
21 Feb 2023
Density-Softmax: Efficient Test-time Model for Uncertainty Estimation and Robustness under Distribution Shifts
International Conference on Machine Learning (ICML), 2023
H. Bui
Anqi Liu
OOD
UQCV
589
9
0
13 Feb 2023
Multiplier Bootstrap-based Exploration
International Conference on Machine Learning (ICML), 2023
Runzhe Wan
Haoyu Wei
Branislav Kveton
R. Song
208
3
0
03 Feb 2023
Thompson Sampling with Diffusion Generative Prior
International Conference on Machine Learning (ICML), 2023
Yu-Guan Hsieh
S. Kasiviswanathan
Branislav Kveton
Patrick Blobaum
DiffM
268
6
0
12 Jan 2023
Uncertainty Quantification for Deep Neural Networks: An Empirical Comparison and Usage Guidelines
Software testing, verification & reliability (STVR), 2022
Michael Weiss
Paolo Tonella
BDL
UQCV
178
13
0
14 Dec 2022
Latent Bottlenecked Attentive Neural Processes
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Leo Feng
Hossein Hajimirsadeghi
Yoshua Bengio
Mohamed Osama Ahmed
BDL
226
27
0
15 Nov 2022
History-Based, Bayesian, Closure for Stochastic Parameterization: Application to Lorenz '96
Mohamed Aziz Bhouri
Pierre Gentine
AI4TS
AI4CE
191
6
0
26 Oct 2022
Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees
Neural Information Processing Systems (NeurIPS), 2022
Andrea Tirinzoni
Matteo Papini
Ahmed Touati
A. Lazaric
Matteo Pirotta
259
6
0
24 Oct 2022
Maximum entropy exploration in contextual bandits with neural networks and energy based models
A. Elwood
Marco Leonardi
A. Mohamed
A. Rozza
202
2
0
12 Oct 2022
The Neural Process Family: Survey, Applications and Perspectives
Saurav Jha
Dong Gong
Xuesong Wang
Richard Turner
Weitong Chen
BDL
480
27
0
01 Sep 2022
BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks
European Conference on Computer Vision (ECCV), 2022
Uddeshya Upadhyay
Shyamgopal Karthik
Yanbei Chen
Goran Frehse
Zeynep Akata
UQCV
BDL
256
26
0
14 Jul 2022
Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence Modeling
International Conference on Machine Learning (ICML), 2022
Tung Nguyen
Aditya Grover
BDL
UQCV
299
136
0
09 Jul 2022
Bayesian approaches for Quantifying Clinicians' Variability in Medical Image Quantification
Jaeik Jeon
Yeonggul Jang
Youngtaek Hong
H. Shim
Sekeun Kim
167
1
0
05 Jul 2022
SLOVA: Uncertainty Estimation Using Single Label One-Vs-All Classifier
Applied Soft Computing (ASC), 2022
Bartosz Wójcik
J. Grela
Marek Śmieja
Krzysztof Misztal
Jacek Tabor
UQCV
297
4
0
28 Jun 2022
POEM: Out-of-Distribution Detection with Posterior Sampling
International Conference on Machine Learning (ICML), 2022
Yifei Ming
Ying Fan
Shouqing Yang
OODD
288
140
0
28 Jun 2022
Langevin Monte Carlo for Contextual Bandits
International Conference on Machine Learning (ICML), 2022
Pan Xu
Hongkai Zheng
Eric Mazumdar
Kamyar Azizzadenesheli
Anima Anandkumar
206
33
0
22 Jun 2022
Generative Pretraining for Black-Box Optimization
International Conference on Machine Learning (ICML), 2022
S. Krishnamoorthy
Satvik Mashkaria
Aditya Grover
OffRL
AI4CE
520
38
0
22 Jun 2022
A Contextual Combinatorial Semi-Bandit Approach to Network Bottleneck Identification
International Conference on Information and Knowledge Management (CIKM), 2022
F. Hoseini
Niklas Åkerblom
M. Chehreghani
185
3
0
16 Jun 2022
How to talk so AI will learn: Instructions, descriptions, and autonomy
Neural Information Processing Systems (NeurIPS), 2022
T. Sumers
Robert D. Hawkins
Mark K. Ho
Thomas Griffiths
Dylan Hadfield-Menell
LM&Ro
469
27
0
16 Jun 2022
Excess risk analysis for epistemic uncertainty with application to variational inference
Futoshi Futami
Tomoharu Iwata
N. Ueda
Issei Sato
Masashi Sugiyama
UQCV
313
1
0
02 Jun 2022
Provably and Practically Efficient Neural Contextual Bandits
International Conference on Machine Learning (ICML), 2022
Sudeep Salgia
Sattar Vakili
Qing Zhao
248
11
0
31 May 2022
Pervasive Machine Learning for Smart Radio Environments Enabled by Reconfigurable Intelligent Surfaces
Proceedings of the IEEE (Proc. IEEE), 2022
G. C. Alexandropoulos
Kyriakos Stylianopoulos
Chongwen Huang
Chau Yuen
M. Bennis
Mérouane Debbah
206
114
0
08 May 2022
A Deep Bayesian Bandits Approach for Anticancer Therapy: Exploration via Functional Prior
Mingyu Lu
Yifang Chen
Su-In Lee
139
0
0
05 May 2022
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness
Journal of machine learning research (JMLR), 2022
J. Liu
Shreyas Padhy
Jie Jessie Ren
Zi Lin
Yeming Wen
Ghassen Jerfel
Zachary Nado
Jasper Snoek
Dustin Tran
Balaji Lakshminarayanan
UQCV
BDL
492
68
0
01 May 2022
Deep Ensemble as a Gaussian Process Approximate Posterior
Zhijie Deng
Feng Zhou
Jianfei Chen
Guoqiang Wu
Jun Zhu
UQCV
189
5
0
30 Apr 2022
Reward-Biased Maximum Likelihood Estimation for Neural Contextual Bandits
AAAI Conference on Artificial Intelligence (AAAI), 2022
Yu-Heng Hung
Ping-Chun Hsieh
233
2
0
08 Mar 2022
Scalable Uncertainty Quantification for Deep Operator Networks using Randomized Priors
Computer Methods in Applied Mechanics and Engineering (CMAME), 2022
Jianlong Wu
Georgios Kissas
P. Perdikaris
BDL
UQCV
275
50
0
06 Mar 2022
Residual Bootstrap Exploration for Stochastic Linear Bandit
Conference on Uncertainty in Artificial Intelligence (UAI), 2022
Shuang Wu
ChiHua Wang
Yuantong Li
Guang Cheng
198
9
0
23 Feb 2022
Fast online inference for nonlinear contextual bandit based on Generative Adversarial Network
Yun-Da Tsai
Shou-De Lin
184
6
0
17 Feb 2022
Designing Closed Human-in-the-loop Deferral Pipelines
Vijay Keswani
Matthew Lease
K. Kenthapadi
OffRL
240
12
0
09 Feb 2022
Maximum Likelihood Uncertainty Estimation: Robustness to Outliers
Deebul Nair
Nico Hochgeschwender
Miguel A. Olivares-Mendez
OOD
238
9
0
03 Feb 2022
Evaluating Deep Vs. Wide & Deep Learners As Contextual Bandits For Personalized Email Promo Recommendations
A. A. Kocherzhenko
Nirmal Sobha Kartha
Tengfei Li
Hsin-Yi Shih
Shih
Marco Mandic
Mike Fuller
Arshak Navruzyan
162
0
0
31 Jan 2022
Neural Collaborative Filtering Bandits via Meta Learning
Yikun Ban
Yunzhe Qi
Tianxin Wei
Jingrui He
OffRL
175
9
0
31 Jan 2022
Optimal Regret Is Achievable with Bounded Approximate Inference Error: An Enhanced Bayesian Upper Confidence Bound Framework
Neural Information Processing Systems (NeurIPS), 2022
Ziyi Huang
Henry Lam
A. Meisami
Haofeng Zhang
376
4
0
31 Jan 2022
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