Marginally calibrated response distributions for end-to-end learning in autonomous driving

3 October 2021

Papers citing "Marginally calibrated response distributions for end-to-end learning in autonomous driving"

39 / 39 papers shown

Title
Implicit copula variational inference M. Smith Rubén Loaiza-Maya 32 7 0 18 Nov 2021
Flexible Variational Bayes based on a Copula of a Mixture David Gunawan Robert Kohn David J. Nott 62 12 0 28 Jun 2021
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Alexey Dosovitskiy Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai ... Matthias Minderer G. Heigold Sylvain Gelly Jakob Uszkoreit N. Houlsby ViT 634 41,003 0 22 Oct 2020
Deep Distributional Time Series Models and the Probabilistic Forecasting of Intraday Electricity Prices Nadja Klein M. Smith David J. Nott BDL AI4TS 44 25 0 05 Oct 2020
Bayesian Deep Ensembles via the Neural Tangent Kernel Bobby He Balaji Lakshminarayanan Yee Whye Teh BDL UQCV 53 120 0 11 Jul 2020
A Comparison of Uncertainty Estimation Approaches in Deep Learning Components for Autonomous Vehicle Applications F. Arnez H. Espinoza A. Radermacher Franccois Terrier UQCV 40 30 0 26 Jun 2020
Modeling Teacher-Student Techniques in Deep Neural Networks for Knowledge Distillation Sajjad Abbasi M. Hajabdollahi N. Karimi S. Samavi 33 29 0 31 Dec 2019
Benchmarking the Neural Linear Model for Regression Sebastian W. Ober C. Rasmussen BDL 67 42 0 18 Dec 2019
Marginally-calibrated deep distributional regression Nadja Klein David J. Nott M. Smith UQCV 55 14 0 26 Aug 2019
Bayesian Batch Active Learning as Sparse Subset Approximation Robert Pinsler Jonathan Gordon Eric T. Nalisnick José Miguel Hernández-Lobato UQCV 47 132 0 06 Aug 2019
Confidence Calibration for Convolutional Neural Networks Using Structured Dropout Zhilu Zhang Adrian Dalca M. Sabuncu UQCV BDL 49 48 0 23 Jun 2019
High-dimensional copula variational approximation through transformation M. Smith Rubén Loaiza-Maya David J. Nott 56 33 0 16 Apr 2019
A Commute in Data: The comma2k19 Dataset H. Schafer Eder Santana A. Haden R. Biasini 3DV 49 71 0 14 Dec 2018
Evaluating Uncertainty Quantification in End-to-End Autonomous Driving Control Rhiannon Michelmore Marta Kwiatkowska Y. Gal UQCV 45 102 0 16 Nov 2018
Beyond expectation: Deep joint mean and quantile regression for spatio-temporal problems Filipe Rodrigues Francisco Câmara Pereira AI4TS 111 95 0 27 Aug 2018
Accurate Uncertainties for Deep Learning Using Calibrated Regression Volodymyr Kuleshov Nathan Fenner Stefano Ermon BDL UQCV 193 632 0 01 Jul 2018
Bayesian Deep Net GLM and GLMM Minh-Ngoc Tran Nghia Nguyen David J. Nott Robert Kohn BDL 111 75 0 25 May 2018
Spatial Uncertainty Sampling for End-to-End Control Alexander Amini A. Soleimany S. Karaman Daniela Rus UQCV BDL 45 30 0 13 May 2018
Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling C. Riquelme George Tucker Jasper Snoek BDL 69 365 0 26 Feb 2018
High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach Tim Pearce Mohamed H. Zaki Alexandra Brintrup A. Neely UQCV 253 280 0 20 Feb 2018
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 299 5,827 0 14 Jun 2017
Deep Learning: A Bayesian Perspective Nicholas G. Polson Vadim Sokolov BDL 82 117 0 01 Jun 2017
Reducing Reparameterization Gradient Variance Andrew C. Miller N. Foti Alexander DÁmour Ryan P. Adams 61 84 0 22 May 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 352 4,705 0 15 Mar 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 822 5,811 0 05 Dec 2016
End-to-end Learning of Driving Models from Large-scale Video Datasets Huazhe Xu Yang Gao Feng Yu Trevor Darrell 136 825 0 04 Dec 2016
End to End Learning for Self-Driving Cars Mariusz Bojarski D. Testa Daniel Dworakowski Bernhard Firner B. Flepp ... Urs Muller Jiakai Zhang Xin Zhang Jake Zhao Karol Zieba SSL 100 4,167 0 25 Apr 2016
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems Martín Abadi Ashish Agarwal P. Barham E. Brevdo Zhiwen Chen ... Pete Warden Martin Wattenberg Martin Wicke Yuan Yu Xiaoqiang Zheng 269 11,152 0 14 Mar 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 818 9,306 0 06 Jun 2015
Weight Uncertainty in Neural Networks Charles Blundell Julien Cornebise Koray Kavukcuoglu Daan Wierstra UQCV BDL 185 1,886 0 20 May 2015
DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving Chenyi Chen Ari Seff A. Kornhauser Jianxiong Xiao 99 1,762 0 01 May 2015
Scalable Bayesian Optimization Using Deep Neural Networks Jasper Snoek Oren Rippel Kevin Swersky Ryan Kiros N. Satish N. Sundaram Md. Mostofa Ali Patwary P. Prabhat Ryan P. Adams BDL UQCV 92 1,043 0 19 Feb 2015
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 450 16,933 0 20 Dec 2013
RNADE: The real-valued neural autoregressive density-estimator Benigno Uria Iain Murray Hugo Larochelle 100 238 0 02 Jun 2013
ADADELTA: An Adaptive Learning Rate Method Matthew D. Zeiler ODL 150 6,624 0 22 Dec 2012
Stochastic Variational Inference Matt Hoffman David M. Blei Chong-Jun Wang John Paisley BDL 252 2,621 0 29 Jun 2012
MCMC using Hamiltonian dynamics Radford M. Neal 290 3,281 0 09 Jun 2012
Combining Predictive Distributions T. Gneiting Roopesh Ranjan 65 223 0 08 Jun 2011
Copula Processes A. Wilson Zoubin Ghahramani 179 113 0 07 Jun 2010