Why M Heads are Better than One: Training a Diverse Ensemble of Deep
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Why M Heads are Better than One: Training a Diverse Ensemble of Deep Networks

19 November 2015

Senthil Purushwalkam

Michael Cogswell

David J. Crandall

Papers citing "Why M Heads are Better than One: Training a Diverse Ensemble of Deep Networks"

18 / 18 papers shown

Title
Self-Ensembling Gaussian Splatting for Few-Shot Novel View Synthesis Chen Zhao Xuan Wang Tong Zhang Saqib Javed Mathieu Salzmann 3DGS 512 0 0 13 Mar 2025
Fairness of Deep Ensembles: On the interplay between per-group task difficulty and under-representation Estanislao Claucich Sara Hooker Diego H. Milone Enzo Ferrante Rodrigo Echeveste FedML 86 0 0 24 Jan 2025
Early Failure Detection in Autonomous Surgical Soft-Tissue Manipulation via Uncertainty Quantification Jordan Thompson Ronald Koe Anthony Le Gabriella Goodman Daniel S. Brown Alan Kuntz 137 2 0 17 Jan 2025
TabM: Advancing Tabular Deep Learning with Parameter-Efficient Ensembling Yury Gorishniy Akim Kotelnikov Artem Babenko LMTD MoE 251 11 0 31 Oct 2024
Network Fission Ensembles for Low-Cost Self-Ensembles Hojung Lee Jong-Seok Lee UQCV 134 1 0 05 Aug 2024
Visual Saliency Prediction Using a Mixture of Deep Neural Networks Samuel F. Dodge Lina Karam FAtt 91 48 0 01 Feb 2017
Very Deep Multilingual Convolutional Neural Networks for LVCSR Tom Sercu Christian Puhrsch Brian Kingsbury Yann LeCun 55 224 0 29 Sep 2015
Fast R-CNN Ross B. Girshick ObjD 303 25,051 0 30 Apr 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 359 19,643 0 09 Mar 2015
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 248 4,667 0 21 Dec 2014
Learning with Pseudo-Ensembles Philip Bachman O. Alsharif Doina Precup 81 598 0 16 Dec 2014
Going Deeper with Convolutions Christian Szegedy Wei Liu Yangqing Jia P. Sermanet Scott E. Reed Dragomir Anguelov D. Erhan Vincent Vanhoucke Andrew Rabinovich 465 43,658 0 17 Sep 2014
Sequence to Sequence Learning with Neural Networks Ilya Sutskever Oriol Vinyals Quoc V. Le AIMat 434 20,553 0 10 Sep 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.6K 100,348 0 04 Sep 2014
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 39,525 0 01 Sep 2014
Network In Network Min Lin Qiang Chen Shuicheng Yan 291 6,275 0 16 Dec 2013
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 595 15,882 0 12 Nov 2013
Rich feature hierarchies for accurate object detection and semantic segmentation Ross B. Girshick Jeff Donahue Trevor Darrell Jitendra Malik ObjD 289 26,186 0 11 Nov 2013