von Mises-Fisher Loss: An Exploration of Embedding Geometries for Supervised Learning

29 March 2021

Papers citing "von Mises-Fisher Loss: An Exploration of Embedding Geometries for Supervised Learning"

9 / 9 papers shown

Title
A unifying mutual information view of metric learning: cross-entropy vs. pairwise losses Malik Boudiaf Jérôme Rony Imtiaz Masud Ziko Eric Granger M. Pedersoli Pablo Piantanida Ismail Ben Ayed SSL 33 159 0 19 Mar 2020
Hyperbolic Image Embeddings Valentin Khrulkov L. Mirvakhabova E. Ustinova Ivan Oseledets Victor Lempitsky 25 288 0 03 Apr 2019
Modeling Uncertainty with Hedged Instance Embedding Seong Joon Oh Kevin Patrick Murphy Jiyan Pan Joseph Roth Florian Schroff Andrew C. Gallagher UQCV 380 70 0 30 Sep 2018
Hyperspherical Variational Auto-Encoders Tim R. Davidson Luca Falorsi Nicola De Cao Thomas Kipf Jakub M. Tomczak DRL BDL 66 381 0 03 Apr 2018
Learning to Compare: Relation Network for Few-Shot Learning Flood Sung Yongxin Yang Li Zhang Tao Xiang Philip Torr Timothy M. Hospedales 125 4,035 0 16 Nov 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 25 8,807 0 25 Aug 2017
L2-constrained Softmax Loss for Discriminative Face Verification Rajeev Ranjan Carlos D. Castillo Rama Chellappa CVBM 58 452 0 28 Mar 2017
Matching Networks for One Shot Learning Oriol Vinyals Charles Blundell Timothy Lillicrap Koray Kavukcuoglu Daan Wierstra VLM 184 7,286 0 13 Jun 2016
FaceNet: A Unified Embedding for Face Recognition and Clustering Florian Schroff Dmitry Kalenichenko James Philbin 3DH 181 13,079 0 12 Mar 2015