Concrete Dropout

22 May 2017

Alex Kendall

Papers citing "Concrete Dropout"

50 / 133 papers shown

Title
Fast online inference for nonlinear contextual bandit based on Generative Adversarial Network Yun-Da Tsai Shou-De Lin 43 5 0 17 Feb 2022
A deep mixture density network for outlier-corrected interpolation of crowd-sourced weather data Charlie Kirkwood T. Economou H. Odbert N. Pugeault 15 0 0 25 Jan 2022
Improving Subgraph Recognition with Variational Graph Information Bottleneck Junchi Yu Jie Cao Ran He 22 53 0 18 Dec 2021
Calibrated and Sharp Uncertainties in Deep Learning via Density Estimation Volodymyr Kuleshov Shachi Deshpande UQCV BDL 38 33 0 14 Dec 2021
Probabilistic Approach for Road-Users Detection Gledson Melotti Weihao Lu Pedro Conde Dezong Zhao A. Asvadi Nuno Gonçalves C. Premebida 27 2 0 02 Dec 2021
Uncertainty Aware Proposal Segmentation for Unknown Object Detection Yimeng Li Jana Kosecka UQCV 36 19 0 25 Nov 2021
MC-CIM: Compute-in-Memory with Monte-Carlo Dropouts for Bayesian Edge Intelligence Priyesh Shukla Shamma Nasrin Nastaran Darabi Wilfred Gomes A. R. Trivedi 28 17 0 13 Nov 2021
A Survey on Epistemic (Model) Uncertainty in Supervised Learning: Recent Advances and Applications Xinlei Zhou Han Liu Farhad Pourpanah T. Zeng Xizhao Wang UQCV UD 24 58 0 03 Nov 2021
Which Model to Trust: Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms for Continuous Control Tasks Giacomo Arcieri David Wölfle Eleni Chatzi OffRL 27 5 0 25 Oct 2021
Pathologies in priors and inference for Bayesian transformers Tristan Cinquin Alexander Immer Max Horn Vincent Fortuin UQCV BDL MedIm 34 9 0 08 Oct 2021
Propagating State Uncertainty Through Trajectory Forecasting Boris Ivanovic Yifeng Lin Shubham Shrivastava Punarjay Chakravarty Marco Pavone 78 18 0 07 Oct 2021
Probabilistic Metamodels for an Efficient Characterization of Complex Driving Scenarios Max Winkelmann Mike Kohlhoff H. Tadjine Steffen Müller 29 9 0 06 Oct 2021
Dropout Q-Functions for Doubly Efficient Reinforcement Learning Takuya Hiraoka Takahisa Imagawa Taisei Hashimoto Takashi Onishi Yoshimasa Tsuruoka 11 104 0 05 Oct 2021
A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning Iris A. M. Huijben W. Kool Max B. Paulus Ruud J. G. van Sloun 28 93 0 04 Oct 2021
Introspective Robot Perception using Smoothed Predictions from Bayesian Neural Networks Jianxiang Feng M. Durner Zoltán-Csaba Márton Ferenc Bálint-Benczédi Rudolph Triebel UQCV BDL 13 11 0 27 Sep 2021
A framework for benchmarking uncertainty in deep regression F. Schmähling Jörg Martin Clemens Elster UQCV 38 8 0 10 Sep 2021
The Bayesian Learning Rule Mohammad Emtiyaz Khan Håvard Rue BDL 63 73 0 09 Jul 2021
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 59 1,111 0 07 Jul 2021
Improving Uncertainty Calibration of Deep Neural Networks via Truth Discovery and Geometric Optimization Chunwei Ma Ziyun Huang Jiayi Xian Mingchen Gao Jinhui Xu UQCV 33 14 0 25 Jun 2021
Taxonomy of Machine Learning Safety: A Survey and Primer Sina Mohseni Haotao Wang Zhiding Yu Chaowei Xiao Zhangyang Wang J. Yadawa 21 31 0 09 Jun 2021
Debiasing a First-order Heuristic for Approximate Bi-level Optimization Valerii Likhosherstov Xingyou Song K. Choromanski Jared Davis Adrian Weller AI4CE 19 5 0 04 Jun 2021
Quantifying Uncertainty in Deep Spatiotemporal Forecasting Dongxian Wu Liyao (Mars) Gao X. Xiong Matteo Chinazzi Alessandro Vespignani Yi Ma Rose Yu AI4TS 13 68 0 25 May 2021
Correlated Input-Dependent Label Noise in Large-Scale Image Classification Mark Collier Basil Mustafa Efi Kokiopoulou Rodolphe Jenatton Jesse Berent NoLa 181 53 0 19 May 2021
Learning Uncertainty with Artificial Neural Networks for Improved Remaining Time Prediction of Business Processes Hans Weytjens Jochen De Weerdt BDL 25 8 0 12 May 2021
Heterogeneous-Agent Trajectory Forecasting Incorporating Class Uncertainty Boris Ivanovic Kuan-Hui Lee P. Tokmakov Blake Wulfe R. McAllister Adrien Gaidon Marco Pavone 22 35 0 26 Apr 2021
Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations Pau Rodríguez López Massimo Caccia Alexandre Lacoste L. Zamparo I. Laradji Laurent Charlin David Vazquez AAML 37 55 0 18 Mar 2021
Contextual Dropout: An Efficient Sample-Dependent Dropout Module Xinjie Fan Shujian Zhang Korawat Tanwisuth Xiaoning Qian Mingyuan Zhou OOD BDL UQCV 30 27 0 06 Mar 2021
Uncertainty Quantification by Ensemble Learning for Computational Optical Form Measurements L. Hoffmann I. Fortmeier Clemens Elster UQCV 25 28 0 01 Mar 2021
LocalDrop: A Hybrid Regularization for Deep Neural Networks Ziqing Lu Chang Xu Bo Du Takashi Ishida Lefei Zhang Masashi Sugiyama 33 14 0 01 Mar 2021
DeepGLEAM: A hybrid mechanistic and deep learning model for COVID-19 forecasting Dongxian Wu Liyao (Mars) Gao X. Xiong Matteo Chinazzi Alessandro Vespignani Yi Ma Rose Yu FedML 22 27 0 12 Feb 2021
Run-Time Monitoring of Machine Learning for Robotic Perception: A Survey of Emerging Trends Q. Rahman Peter Corke Feras Dayoub OOD 29 51 0 05 Jan 2021
On Batch Normalisation for Approximate Bayesian Inference Jishnu Mukhoti P. Dokania Philip Torr Y. Gal BDL UQCV 29 4 0 24 Dec 2020
Learning Prediction Intervals for Model Performance Benjamin Elder Matthew Arnold Anupama Murthi Jirí Navrátil 19 10 0 15 Dec 2020
A Review and Comparative Study on Probabilistic Object Detection in Autonomous Driving Di Feng Ali Harakeh Steven Waslander Klaus C. J. Dietmayer AAML UQCV EDL 24 223 0 20 Nov 2020
Predictive Monitoring with Logic-Calibrated Uncertainty for Cyber-Physical Systems Meiyi Ma John A. Stankovic E. Bartocci Lu Feng 26 24 0 31 Oct 2020
Bayesian Attention Modules Xinjie Fan Shujian Zhang Bo Chen Mingyuan Zhou 117 59 0 20 Oct 2020
Perceiving Humans: from Monocular 3D Localization to Social Distancing Lorenzo Bertoni S. Kreiss Alexandre Alahi 31 46 0 01 Sep 2020
Vision-Based Goal-Conditioned Policies for Underwater Navigation in the Presence of Obstacles Travis Manderson J. A. G. Higuera Stefan Wapnick J. Tremblay Florian Shkurti D. Meger Gregory Dudek 19 50 0 29 Jun 2020
Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift Alex J. Chan Ahmed Alaa Zhaozhi Qian M. Schaar UQCV BDL OOD 28 38 0 26 Jun 2020
Bayesian Neural Networks: An Introduction and Survey Ethan Goan Clinton Fookes BDL UQCV 35 199 0 22 Jun 2020
Calibration of Model Uncertainty for Dropout Variational Inference M. Laves Sontje Ihler Karl-Philipp Kortmann T. Ortmaier BDL UQCV 32 18 0 20 Jun 2020
Detecting unusual input to neural networks Jörg Martin Clemens Elster AAML 17 7 0 15 Jun 2020
UFO-BLO: Unbiased First-Order Bilevel Optimization Valerii Likhosherstov Xingyou Song K. Choromanski Jared Davis Adrian Weller 32 7 0 05 Jun 2020
Designing Accurate Emulators for Scientific Processes using Calibration-Driven Deep Models Jayaraman J. Thiagarajan Bindya Venkatesh Rushil Anirudh P. Bremer J. Gaffney G. Anderson B. Spears 13 21 0 05 May 2020
A Simple Probabilistic Method for Deep Classification under Input-Dependent Label Noise Mark Collier Basil Mustafa Efi Kokiopoulou Rodolphe Jenatton Jesse Berent UQCV NoLa 41 0 0 15 Mar 2020
Estimating Uncertainty Intervals from Collaborating Networks Tianhui Zhou Yitong Li Yuan Wu David Carlson UQCV 27 15 0 12 Feb 2020
Uncertainty-Based Out-of-Distribution Classification in Deep Reinforcement Learning Andreas Sedlmeier Thomas Gabor Thomy Phan Lenz Belzner Claudia Linnhoff-Popien 21 25 0 31 Dec 2019
TRADI: Tracking deep neural network weight distributions for uncertainty estimation Gianni Franchi Andrei Bursuc Emanuel Aldea Séverine Dubuisson Isabelle Bloch UQCV 26 51 0 24 Dec 2019
Angular Visual Hardness Beidi Chen Weiyang Liu Zhiding Yu Jan Kautz Anshumali Shrivastava Animesh Garg Anima Anandkumar AAML 43 51 0 04 Dec 2019
Learning with Multiplicative Perturbations Xiulong Yang Shihao Ji AAML 30 4 0 04 Dec 2019