Benchmarking the Neural Linear Model for Regression

18 December 2019

Papers citing "Benchmarking the Neural Linear Model for Regression"

14 / 14 papers shown

Title
Probabilistic Unrolling: Scalable, Inverse-Free Maximum Likelihood Estimation for Latent Gaussian Models Alexander Lin Bahareh Tolooshams Yves Atchadé Demba E. Ba 38 1 0 05 Jun 2023
FineMorphs: Affine-diffeomorphic sequences for regression Michele Lohr L. Younes 34 0 0 26 May 2023
Do Bayesian Neural Networks Need To Be Fully Stochastic? Mrinank Sharma Sebastian Farquhar Eric T. Nalisnick Tom Rainforth BDL 28 52 0 11 Nov 2022
A Framework and Benchmark for Deep Batch Active Learning for Regression David Holzmüller Viktor Zaverkin Johannes Kastner Ingo Steinwart UQCV BDL GP 31 34 0 17 Mar 2022
Uncertainty Quantification in Neural Differential Equations Olga Graf P. Flores P. Protopapas K. Pichara UQCV AI4CE 37 7 0 08 Nov 2021
Marginally calibrated response distributions for end-to-end learning in autonomous driving Clara Hoffmann Nadja Klein 26 2 0 03 Oct 2021
Trust Your Robots! Predictive Uncertainty Estimation of Neural Networks with Sparse Gaussian Processes Jongseo Lee Jianxiang Feng Matthias Humt M. Müller Rudolph Triebel UQCV 55 21 0 20 Sep 2021
Bayesian Deep Basis Fitting for Depth Completion with Uncertainty Chao Qu Wenxin Liu Camillo J Taylor UQCV BDL 31 31 0 29 Mar 2021
NOMU: Neural Optimization-based Model Uncertainty Jakob Heiss Jakob Weissteiner Hanna Wutte Sven Seuken Josef Teichmann BDL 42 19 0 26 Feb 2021
The Promises and Pitfalls of Deep Kernel Learning Sebastian W. Ober C. Rasmussen Mark van der Wilk UQCV BDL 26 107 0 24 Feb 2021
Uncertainty-Aware (UNA) Bases for Deep Bayesian Regression Using Multi-Headed Auxiliary Networks Sujay Thakur Cooper Lorsung Yaniv Yacoby Finale Doshi-Velez Weiwei Pan BDL UQCV 33 4 0 21 Jun 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 42 279 0 24 Feb 2020
Marginally-calibrated deep distributional regression Nadja Klein David J. Nott M. Smith UQCV 37 14 0 26 Aug 2019
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 289 9,167 0 06 Jun 2015