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1906.08312
Cited By
Calibrated Model-Based Deep Reinforcement Learning
19 June 2019
Ali Malik
Volodymyr Kuleshov
Jiaming Song
Danny Nemer
Harlan Seymour
Stefano Ermon
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Papers citing
"Calibrated Model-Based Deep Reinforcement Learning"
20 / 20 papers shown
Title
Zero-shot Model-based Reinforcement Learning using Large Language Models
Abdelhakim Benechehab
Youssef Attia El Hili
Ambroise Odonnat
Oussama Zekri
Albert Thomas
Giuseppe Paolo
Maurizio Filippone
I. Redko
Balázs Kégl
OffRL
75
1
0
17 Feb 2025
Calibrated Probabilistic Forecasts for Arbitrary Sequences
Charles Marx
Volodymyr Kuleshov
Stefano Ermon
AI4TS
44
1
0
27 Sep 2024
Cross-Domain Policy Adaptation by Capturing Representation Mismatch
Jiafei Lyu
Chenjia Bai
Jingwen Yang
Zongqing Lu
Xiu Li
30
9
0
24 May 2024
Calibration of Continual Learning Models
Lanpei Li
Elia Piccoli
Andrea Cossu
Davide Bacciu
Vincenzo Lomonaco
CLL
45
2
0
11 Apr 2024
Modular Conformal Calibration
Charles Marx
Shengjia Zhao
Willie Neiswanger
Stefano Ermon
36
15
0
23 Jun 2022
A Verification Framework for Certifying Learning-Based Safety-Critical Aviation Systems
Ali Baheri
Hao Ren
B. Johnson
Pouria Razzaghi
Peng Wei
21
5
0
09 May 2022
Approaching sales forecasting using recurrent neural networks and transformers
Iván Vallés-Pérez
E. Soria-Olivas
M. Martínez-Sober
Antonio J. Serrano
J. Gómez-Sanchís
Fernando Mateo
AI4TS
24
36
0
16 Apr 2022
Calibrated and Sharp Uncertainties in Deep Learning via Density Estimation
Volodymyr Kuleshov
Shachi Deshpande
UQCV
BDL
38
33
0
14 Dec 2021
Online Calibrated and Conformal Prediction Improves Bayesian Optimization
Shachi Deshpande
Charles Marx
Volodymyr Kuleshov
13
7
0
08 Dec 2021
PAC Prediction Sets Under Covariate Shift
Sangdon Park
Yan Sun
Insup Lee
Osbert Bastani
32
43
0
17 Jun 2021
Offline Reinforcement Learning as One Big Sequence Modeling Problem
Michael Janner
Qiyang Li
Sergey Levine
OffRL
66
649
0
03 Jun 2021
Safety Enhancement for Deep Reinforcement Learning in Autonomous Separation Assurance
Wei Guo
Marc Brittain
Peng Wei
31
18
0
05 May 2021
Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning
Sebastian Curi
Ilija Bogunovic
Andreas Krause
39
17
0
18 Mar 2021
Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs
Cheng Wang
Carolin (Haas) Lawrence
Mathias Niepert
UQCV
29
10
0
24 Nov 2020
Individual Calibration with Randomized Forecasting
Shengjia Zhao
Tengyu Ma
Stefano Ermon
16
57
0
18 Jun 2020
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning
Sebastian Curi
Felix Berkenkamp
Andreas Krause
33
82
0
15 Jun 2020
PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction
Sangdon Park
Osbert Bastani
Nikolai Matni
Insup Lee
UQCV
141
68
0
31 Dec 2019
Verified Uncertainty Calibration
Ananya Kumar
Percy Liang
Tengyu Ma
27
346
0
23 Sep 2019
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
276
5,683
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
287
9,156
0
06 Jun 2015
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