Stochastic Filter Groups for Multi-Task CNNs: Learning Specialist and
Generalist Convolution Kernels

Stochastic Filter Groups for Multi-Task CNNs: Learning Specialist and Generalist Convolution Kernels

26 August 2019

Felix J. S. Bragman

Sebastien Ourselin

Daniel C. Alexander

M. Jorge Cardoso

Papers citing "Stochastic Filter Groups for Multi-Task CNNs: Learning Specialist and Generalist Convolution Kernels"

14 / 14 papers shown

Title
E2E-MFD: Towards End-to-End Synchronous Multimodal Fusion Detection Jiaqing Zhang Mingxiang Cao Weiying Xie Jie Lei Daixun Li Wenbo Huang Yunsong Li Xue Yang 48 4 0 28 Jan 2025
Swiss Army Knife: Synergizing Biases in Knowledge from Vision Foundation Models for Multi-Task Learning Yuxiang Lu Shengcao Cao Yu-xiong Wang 45 1 0 18 Oct 2024
Towards Modular LLMs by Building and Reusing a Library of LoRAs O. Ostapenko Zhan Su E. Ponti Laurent Charlin Nicolas Le Roux Matheus Pereira Lucas Page-Caccia Alessandro Sordoni MoMe 32 30 0 18 May 2024
Alternate Training of Shared and Task-Specific Parameters for Multi-Task Neural Networks Stefania Bellavia Francesco Della Santa Alessandra Papini 33 0 0 26 Dec 2023
FAMO: Fast Adaptive Multitask Optimization B. Liu Yihao Feng Peter Stone Qian Liu 33 30 0 06 Jun 2023
TMoE-P: Towards the Pareto Optimum for Multivariate Soft Sensors Licheng Pan Hao Wang Zhichao Chen Yuxin Huang Xinggao Liu 10 0 0 21 Feb 2023
Context Label Learning: Improving Background Class Representations in Semantic Segmentation Zeju Li Konstantinos Kamnitsas C. Ouyang Chen Chen Ben Glocker VLM 25 6 0 16 Dec 2022
Highly Scalable Task Grouping for Deep Multi-Task Learning in Prediction of Epigenetic Events Mohammad Shiri Jiangwen Sun 11 1 0 24 Sep 2022
Universal Representations: A Unified Look at Multiple Task and Domain Learning Wei-Hong Li Xialei Liu Hakan Bilen SSL OOD 28 27 0 06 Apr 2022
Learning Multiple Dense Prediction Tasks from Partially Annotated Data Weihong Li Xialei Liu Hakan Bilen 31 39 0 29 Nov 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 24 92 0 04 Oct 2021
Reparameterizing Convolutions for Incremental Multi-Task Learning without Task Interference Menelaos Kanakis David Brüggemann Suman Saha Stamatios Georgoulis Anton Obukhov Luc Van Gool CLL 22 72 0 24 Jul 2020
Maximum Roaming Multi-Task Learning Lucas Pascal Pietro Michiardi Xavier Bost B. Huet Maria A. Zuluaga 17 31 0 17 Jun 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,660 0 05 Dec 2016