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Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning

6 February 2024

Papers citing "Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning"

33 / 33 papers shown

Title
Self Supervised Correlation-based Permutations for Multi-View Clustering Ran Eisenberg Jonathan Svirsky Ofir Lindenbaum 99 2 0 26 Feb 2024
Guided Deep Kernel Learning Idan Achituve Gal Chechik Ethan Fetaya BDL 57 7 0 19 Feb 2023
Auxiliary Learning as an Asymmetric Bargaining Game Aviv Shamsian Aviv Navon Neta Glazer Kenji Kawaguchi Gal Chechik Ethan Fetaya 64 8 0 31 Jan 2023
Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Stochastic Approach H. Fernando Han Shen Miao Liu Subhajit Chaudhury K. Murugesan Tianyi Chen 79 9 0 23 Oct 2022
Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models Nikolaos Dimitriadis P. Frossard Franccois Fleuret 71 25 0 18 Oct 2022
Do Current Multi-Task Optimization Methods in Deep Learning Even Help? Derrick Xin Behrooz Ghorbani Ankush Garg Orhan Firat Justin Gilmer MoMe 122 65 0 23 Sep 2022
Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning Baijiong Lin Feiyang Ye Yu Zhang Ivor W. Tsang 99 99 0 20 Nov 2021
Laplace Redux -- Effortless Bayesian Deep Learning Erik A. Daxberger Agustinus Kristiadi Alexander Immer Runa Eschenhagen Matthias Bauer Philipp Hennig BDL UQCV 221 315 0 28 Jun 2021
Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning Alexander Immer Matthias Bauer Vincent Fortuin Gunnar Rätsch Mohammad Emtiyaz Khan BDL UQCV 130 109 0 11 Apr 2021
Bayesian Neural Network Priors Revisited Vincent Fortuin Adrià Garriga-Alonso Sebastian W. Ober F. Wenzel Gunnar Rätsch Richard Turner Mark van der Wilk Laurence Aitchison BDL UQCV 106 141 0 12 Feb 2021
Deep Learning-Based Human Pose Estimation: A Survey Ce Zheng Wenhan Wu Chong Chen Taojiannan Yang Sijie Zhu Ju Shen N. Kehtarnavaz M. Shah 3DH 193 592 0 24 Dec 2020
Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual Models Zirui Wang Yulia Tsvetkov Orhan Firat Yuan Cao 74 202 0 12 Oct 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 88 289 0 24 Feb 2020
Bayesian Deep Learning and a Probabilistic Perspective of Generalization A. Wilson Pavel Izmailov UQCV BDL OOD 115 656 0 20 Feb 2020
Gradient Surgery for Multi-Task Learning Tianhe Yu Saurabh Kumar Abhishek Gupta Sergey Levine Karol Hausman Chelsea Finn 184 1,228 0 19 Jan 2020
Which Tasks Should Be Learned Together in Multi-task Learning? Trevor Scott Standley Amir Zamir Dawn Chen Leonidas Guibas Jitendra Malik Silvio Savarese 105 517 0 18 May 2019
Ray Interference: a Source of Plateaus in Deep Reinforcement Learning Tom Schaul Diana Borsa Joseph Modayil Razvan Pascanu 70 63 0 25 Apr 2019
MultiNet++: Multi-Stream Feature Aggregation and Geometric Loss Strategy for Multi-Task Learning Sumanth Chennupati Ganesh Sistu S. Yogamani S. Rawashdeh 60 94 0 15 Apr 2019
Fast Graph Representation Learning with PyTorch Geometric Matthias Fey J. E. Lenssen 3DH GNN 3DPC 239 4,364 0 06 Mar 2019
Hierarchical and Interpretable Skill Acquisition in Multi-task Reinforcement Learning Tianmin Shu Caiming Xiong R. Socher OffRL 138 140 0 20 Dec 2017
Routing Networks: Adaptive Selection of Non-linear Functions for Multi-Task Learning Clemens Rosenbaum Tim Klinger Matthew D Riemer 84 247 0 03 Nov 2017
An Overview of Multi-Task Learning in Deep Neural Networks Sebastian Ruder CVBM 159 2,831 0 15 Jun 2017
Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics Alex Kendall Y. Gal R. Cipolla 3DH 272 3,135 0 19 May 2017
Neural Message Passing for Quantum Chemistry Justin Gilmer S. Schoenholz Patrick F. Riley Oriol Vinyals George E. Dahl 598 7,496 0 04 Apr 2017
MoleculeNet: A Benchmark for Molecular Machine Learning Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes C. Geniesse Aneesh S. Pappu K. Leswing Vijay S. Pande OOD 337 1,839 0 02 Mar 2017
Age Progression/Regression by Conditional Adversarial Autoencoder Zhifei Zhang Yang Song Hairong Qi GAN CVBM 87 1,118 0 27 Feb 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 842 5,841 0 05 Dec 2016
Learning Modular Neural Network Policies for Multi-Task and Multi-Robot Transfer Coline Devin Abhishek Gupta Trevor Darrell Pieter Abbeel Sergey Levine OffRL 84 400 0 22 Sep 2016
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 298 4,812 0 04 Jan 2016
Deep Kernel Learning A. Wilson Zhiting Hu Ruslan Salakhutdinov Eric Xing BDL 256 889 0 06 Nov 2015
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 1.7K 39,615 0 01 Sep 2014
Manifold Gaussian Processes for Regression Roberto Calandra Jan Peters C. Rasmussen M. Deisenroth 170 274 0 24 Feb 2014
Expectation Propagation for approximate Bayesian inference T. Minka 137 1,909 0 10 Jan 2013