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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"
31 / 231 papers shown
PHYRE: A New Benchmark for Physical Reasoning
Neural Information Processing Systems (NeurIPS), 2019
A. Bakhtin
Laurens van der Maaten
Justin Johnson
Laura Gustafson
Ross B. Girshick
LRM
230
148
0
15 Aug 2019
Thompson Sampling with Approximate Inference
My Phan
Yasin Abbasi-Yadkori
Justin Domke
153
29
0
14 Aug 2019
Vector Quantized Bayesian Neural Network Inference for Data Streams
AAAI Conference on Artificial Intelligence (AAAI), 2019
Namuk Park
Taekyu Lee
Songkuk Kim
MQ
165
11
0
12 Jul 2019
Ín-Between' Uncertainty in Bayesian Neural Networks
Andrew Y. K. Foong
Yingzhen Li
José Miguel Hernández-Lobato
Richard Turner
BDL
UQCV
195
130
0
27 Jun 2019
Randomized Exploration in Generalized Linear Bandits
International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
Branislav Kveton
Manzil Zaheer
Csaba Szepesvári
Lihong Li
Mohammad Ghavamzadeh
Craig Boutilier
309
104
0
21 Jun 2019
Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates
Neural Information Processing Systems (NeurIPS), 2019
Hugo Penedones
C. Riquelme
Damien Vincent
Hartmut Maennel
Timothy A. Mann
André Barreto
Sylvain Gelly
Gergely Neu
OffRL
173
10
0
19 Jun 2019
Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep Ensembles
AAAI Conference on Artificial Intelligence (AAAI), 2019
Siddhartha Jain
Ge Liu
Jonas W. Mueller
David K Gifford
UQCV
178
66
0
18 Jun 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift
Neural Information Processing Systems (NeurIPS), 2019
Yaniv Ovadia
Emily Fertig
Jie Jessie Ren
Zachary Nado
D. Sculley
Sebastian Nowozin
Joshua V. Dillon
Balaji Lakshminarayanan
Jasper Snoek
UQCV
1.1K
1,919
0
06 Jun 2019
Practical Deep Learning with Bayesian Principles
Neural Information Processing Systems (NeurIPS), 2019
Kazuki Osawa
S. Swaroop
Anirudh Jain
Runa Eschenhagen
Richard Turner
Rio Yokota
Mohammad Emtiyaz Khan
BDL
UQCV
417
266
0
06 Jun 2019
Learning Representations by Humans, for Humans
International Conference on Machine Learning (ICML), 2019
Sophie Hilgard
Nir Rosenfeld
M. Banaji
Jack Cao
David C. Parkes
OCL
HAI
AI4CE
205
29
0
29 May 2019
Field-aware Calibration: A Simple and Empirically Strong Method for Reliable Probabilistic Predictions
The Web Conference (WWW), 2019
Feiyang Pan
Xiang Ao
Pingzhong Tang
Min Lu
Dapeng Liu
Lei Xiao
Qing He
268
27
0
26 May 2019
The Scientific Method in the Science of Machine Learning
Jessica Zosa Forde
Michela Paganini
140
40
0
24 Apr 2019
Empirical Bayes Regret Minimization
Chih-Wei Hsu
Branislav Kveton
Ofer Meshi
Martin Mladenov
Csaba Szepesvári
210
15
0
04 Apr 2019
Meta-Learning surrogate models for sequential decision making
Alexandre Galashov
Jonathan Richard Schwarz
Hyunjik Kim
M. Garnelo
D. Saxton
Pushmeet Kohli
S. M. Ali Eslami
Yee Whye Teh
BDL
OffRL
218
25
0
28 Mar 2019
Perturbed-History Exploration in Stochastic Linear Bandits
Conference on Uncertainty in Artificial Intelligence (UAI), 2019
Branislav Kveton
Csaba Szepesvári
Mohammad Ghavamzadeh
Craig Boutilier
230
47
0
21 Mar 2019
Functional Variational Bayesian Neural Networks
Shengyang Sun
Guodong Zhang
Jiaxin Shi
Roger C. Grosse
BDL
260
257
0
14 Mar 2019
Perturbed-History Exploration in Stochastic Multi-Armed Bandits
International Joint Conference on Artificial Intelligence (IJCAI), 2019
Branislav Kveton
Csaba Szepesvári
Mohammad Ghavamzadeh
Craig Boutilier
178
31
0
26 Feb 2019
Function Space Particle Optimization for Bayesian Neural Networks
International Conference on Learning Representations (ICLR), 2019
Ziyu Wang
Zhaolin Ren
Jun Zhu
Bo Zhang
BDL
190
68
0
26 Feb 2019
Scalable Thompson Sampling via Optimal Transport
Ruiyi Zhang
Zheng Wen
Changyou Chen
Lawrence Carin
OT
213
20
0
19 Feb 2019
Hybrid Models with Deep and Invertible Features
Eric T. Nalisnick
Akihiro Matsukawa
Yee Whye Teh
Dilan Görür
Balaji Lakshminarayanan
BDL
DRL
310
101
0
07 Feb 2019
Functional Regularisation for Continual Learning with Gaussian Processes
International Conference on Learning Representations (ICLR), 2019
Michalis K. Titsias
Jonathan Richard Schwarz
A. G. Matthews
Razvan Pascanu
Yee Whye Teh
CLL
BDL
517
205
0
31 Jan 2019
Deep Neural Linear Bandits: Overcoming Catastrophic Forgetting through Likelihood Matching
Tom Zahavy
Shie Mannor
HAI
229
31
0
24 Jan 2019
Information-Directed Exploration for Deep Reinforcement Learning
Nikolay Nikolov
Johannes Kirschner
Felix Berkenkamp
Andreas Krause
300
77
0
18 Dec 2018
Garbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits
Branislav Kveton
Csaba Szepesvári
Sharan Vaswani
Zheng Wen
Mohammad Ghavamzadeh
Tor Lattimore
348
73
0
13 Nov 2018
Practical Bayesian Learning of Neural Networks via Adaptive Optimisation Methods
Caroline Werther
M. Ferguson
K. Park
Cuixian Chen
Stephen J. Roberts
ODL
149
4
0
08 Nov 2018
contextual: Evaluating Contextual Multi-Armed Bandit Problems in R
Sayed Chhattan Shah
M. Kaptein
CML
165
10
0
06 Nov 2018
Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning
David Janz
Jiri Hron
Przemysław Mazur
Katja Hofmann
José Miguel Hernández-Lobato
Sebastian Tschiatschek
336
54
0
15 Oct 2018
Nonparametric Gaussian Mixture Models for the Multi-Armed Bandit
Iñigo Urteaga
C. Wiggins
315
3
0
08 Aug 2018
VFunc: a Deep Generative Model for Functions
Philip Bachman
Riashat Islam
Alessandro Sordoni
Zafarali Ahmed
VLM
BDL
139
8
0
11 Jul 2018
Neural Processes
M. Garnelo
Jonathan Richard Schwarz
Dan Rosenbaum
Fabio Viola
Danilo Jimenez Rezende
S. M. Ali Eslami
Yee Whye Teh
BDL
UQCV
GP
265
565
0
04 Jul 2018
New Insights into Bootstrapping for Bandits
Sharan Vaswani
Branislav Kveton
Zheng Wen
Anup B. Rao
Mark Schmidt
Yasin Abbasi-Yadkori
233
18
0
24 May 2018
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