Improving Regression Performance with Distributional Losses

12 June 2018

Papers citing "Improving Regression Performance with Distributional Losses"

10 / 10 papers shown

Title
Hyperspherical Normalization for Scalable Deep Reinforcement Learning Hojoon Lee Youngdo Lee Takuma Seno Donghu Kim Peter Stone Jaegul Choo 63 1 0 24 Feb 2025
The Central Role of the Loss Function in Reinforcement Learning Kaiwen Wang Nathan Kallus Wen Sun OffRL 43 7 0 19 Sep 2024
Is Value Functions Estimation with Classification Plug-and-play for Offline Reinforcement Learning? Denis Tarasov Kirill Brilliantov Dmitrii Kharlapenko OffRL 30 2 0 10 Jun 2024
Bigger, Regularized, Optimistic: scaling for compute and sample-efficient continuous control Michal Nauman M. Ostaszewski Krzysztof Jankowski Piotr Milo's Marek Cygan OffRL 37 16 0 25 May 2024
Distributional GFlowNets with Quantile Flows Dinghuai Zhang L. Pan Ricky T. Q. Chen Aaron Courville Yoshua Bengio 29 25 0 11 Feb 2023
Neural Regression For Scale-Varying Targets Adam Khakhar Jacob Buckman 22 1 0 14 Nov 2022
Distributional loss for convolutional neural network regression and application to GNSS multi-path estimation Thomas Gonzalez Antoine Blais Nicolas P. Couellan Christian Ruiz 11 4 0 03 Jun 2022
Human Pose Regression with Residual Log-likelihood Estimation Jiefeng Li Siyuan Bian Ailing Zeng Can Wang Bo Pang Wentao Liu Cewu Lu 16 191 0 23 Jul 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 270 5,660 0 05 Dec 2016
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 233 2,545 0 25 Jan 2016