A Monte Carlo Framework for Calibrated Uncertainty Estimation in Sequence Prediction

30 October 2024

Carlos Fernandez-Granda

Papers citing "A Monte Carlo Framework for Calibrated Uncertainty Estimation in Sequence Prediction"

22 / 22 papers shown

Title
Calibrated Probabilistic Forecasts for Arbitrary Sequences Charles Marx Volodymyr Kuleshov Stefano Ermon AI4TS 67 1 0 27 Sep 2024
Function-Space Regularization in Neural Networks: A Probabilistic Perspective Tim G. J. Rudner Sanyam Kapoor Shikai Qiu A. Wilson 70 13 0 28 Dec 2023
Adaptive Human Trajectory Prediction via Latent Corridors Neerja Thakkar K. Mangalam Andrea V. Bajcsy Jitendra Malik 58 4 0 11 Dec 2023
Neural General Circulation Models for Weather and Climate Dmitrii Kochkov J. Yuval I. Langmore Peter C. Norgaard Jamie A. Smith ... Peter W. Battaglia Alvaro Sanchez-Gonzalez Matthew Willson Michael P. Brenner Stephan Hoyer AI4Cl AI4CE 115 154 0 13 Nov 2023
Deep Learning for Day Forecasts from Sparse Observations Marcin Andrychowicz L. Espeholt Di Li Samier Merchant Alexander Merose Fred Zyda Shreya Agrawal Nal Kalchbrenner AI4Cl 72 66 0 06 Jun 2023
FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators Jaideep Pathak Shashank Subramanian P. Harrington S. Raja Ashesh Chattopadhyay ... Zong-Yi Li Kamyar Azizzadenesheli Pedram Hassanzadeh K. Kashinath Anima Anandkumar AI4Cl 235 693 0 22 Feb 2022
Language Models are Few-Shot Learners Tom B. Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared Kaplan ... Christopher Berner Sam McCandlish Alec Radford Ilya Sutskever Dario Amodei BDL 795 42,055 0 28 May 2020
Mix-n-Match: Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning Jize Zhang B. Kailkhura T. Y. Han UQCV 83 227 0 16 Mar 2020
Calibrating Deep Neural Networks using Focal Loss Jishnu Mukhoti Viveka Kulharia Amartya Sanyal Stuart Golodetz Philip Torr P. Dokania UQCV 81 463 0 21 Feb 2020
Image Captioning: Transforming Objects into Words Simão Herdade Armin Kappeler K. Boakye Joao Soares ViT 116 470 0 14 Jun 2019
A Simple Baseline for Bayesian Uncertainty in Deep Learning Wesley J. Maddox T. Garipov Pavel Izmailov Dmitry Vetrov A. Wilson BDL UQCV 84 808 0 07 Feb 2019
Non-Autoregressive Neural Machine Translation Jiatao Gu James Bradbury Caiming Xiong Victor O.K. Li R. Socher 102 796 0 07 Nov 2017
mixup: Beyond Empirical Risk Minimization Hongyi Zhang Moustapha Cissé Yann N. Dauphin David Lopez-Paz NoLa 280 9,764 0 25 Oct 2017
Proximal Policy Optimization Algorithms John Schulman Filip Wolski Prafulla Dhariwal Alec Radford Oleg Klimov OffRL 499 19,065 0 20 Jul 2017
Age Progression/Regression by Conditional Adversarial Autoencoder Zhifei Zhang Yang Song Hairong Qi GAN CVBM 72 1,113 0 27 Feb 2017
Regularizing Neural Networks by Penalizing Confident Output Distributions Gabriel Pereyra George Tucker J. Chorowski Lukasz Kaiser Geoffrey E. Hinton NoLa 163 1,141 0 23 Jan 2017
Image Captioning with Semantic Attention Quanzeng You Hailin Jin Zhaowen Wang Chen Fang Jiebo Luo VLM 169 1,662 0 12 Mar 2016
Rethinking the Inception Architecture for Computer Vision Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jonathon Shlens Z. Wojna 3DV BDL 883 27,373 0 02 Dec 2015
Continuous control with deep reinforcement learning Timothy Lillicrap Jonathan J. Hunt Alexander Pritzel N. Heess Tom Erez Yuval Tassa David Silver Daan Wierstra 320 13,248 0 09 Sep 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 821 9,318 0 06 Jun 2015
Weight Uncertainty in Neural Networks Charles Blundell Julien Cornebise Koray Kavukcuoglu Daan Wierstra UQCV BDL 187 1,887 0 20 May 2015
Neural Machine Translation by Jointly Learning to Align and Translate Dzmitry Bahdanau Kyunghyun Cho Yoshua Bengio AIMat 558 27,311 0 01 Sep 2014