Recasting Gradient-Based Meta-Learning as Hierarchical Bayes

26 January 2018

Papers citing "Recasting Gradient-Based Meta-Learning as Hierarchical Bayes"

25 / 25 papers shown

Title
Imperative Learning: A Self-supervised Neuro-Symbolic Learning Framework for Robot Autonomy Chen Wang Kaiyi Ji Junyi Geng Zhongqiang Ren Taimeng Fu ... Yi Du Qihang Li Yue Yang Xiao Lin Zhipeng Zhao SSL 129 10 0 28 Jan 2025
Functional Risk Minimization Ferran Alet Clement Gehring Tomás Lozano-Pérez Kenji Kawaguchi Joshua B. Tenenbaum Leslie Pack Kaelbling OffRL 93 0 0 31 Dec 2024
Proxy-informed Bayesian transfer learning with unknown sources Sabina J. Sloman Julien Martinelli Samuel Kaski 81 1 0 05 Nov 2024
Learning to Compare: Relation Network for Few-Shot Learning Flood Sung Yongxin Yang Li Zhang Tao Xiang Philip Torr Timothy M. Hospedales 244 4,035 0 16 Nov 2017
A Simple Neural Attentive Meta-Learner Nikhil Mishra Mostafa Rohaninejad Xi Chen Pieter Abbeel OOD 65 199 0 11 Jul 2017
Few-Shot Learning Through an Information Retrieval Lens Eleni Triantafillou R. Zemel R. Urtasun 54 238 0 09 Jul 2017
Prototypical Networks for Few-shot Learning Jake C. Snell Kevin Swersky R. Zemel 253 8,072 0 15 Mar 2017
Learned Optimizers that Scale and Generalize Olga Wichrowska Niru Maheswaranathan Matthew W. Hoffman Sergio Gomez Colmenarejo Misha Denil Nando de Freitas Jascha Narain Sohl-Dickstein AI4CE 52 284 0 14 Mar 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 781 11,793 0 09 Mar 2017
Meta Networks Tsendsuren Munkhdalai Hong-ye Yu GNN AI4CE 91 1,064 0 02 Mar 2017
Learning to Optimize Neural Nets Ke Li Jitendra Malik 53 131 0 01 Mar 2017
HyperNetworks David R Ha Andrew M. Dai Quoc V. Le 112 1,603 0 27 Sep 2016
Learning to learn by gradient descent by gradient descent Marcin Andrychowicz Misha Denil Sergio Gomez Colmenarejo Matthew W. Hoffman David Pfau Tom Schaul Brendan Shillingford Nando de Freitas 96 2,000 0 14 Jun 2016
Matching Networks for One Shot Learning Oriol Vinyals Charles Blundell Timothy Lillicrap Koray Kavukcuoglu Daan Wierstra VLM 325 7,299 0 13 Jun 2016
Low-shot Visual Recognition by Shrinking and Hallucinating Features Bharath Hariharan Ross B. Girshick VLM 50 49 0 09 Jun 2016
Towards a Neural Statistician Harrison Edwards Amos Storkey BDL 60 428 0 07 Jun 2016
Learning to Optimize Ke Li Jitendra Malik 51 256 0 06 Jun 2016
Early Stopping is Nonparametric Variational Inference D. Maclaurin David Duvenaud Ryan P. Adams BDL 67 95 0 06 Apr 2015
Optimizing Neural Networks with Kronecker-factored Approximate Curvature James Martens Roger C. Grosse ODL 92 999 0 19 Mar 2015
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 391 43,154 0 11 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.2K 149,474 0 22 Dec 2014
New insights and perspectives on the natural gradient method James Martens ODL 66 613 0 03 Dec 2014
Bayesian Multitask Learning with Latent Hierarchies Hal Daumé BDL 56 130 0 09 Aug 2014
Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs Vikash K. Mansinghka Tejas D. Kulkarni Yura N. Perov J. Tenenbaum 144 108 0 29 Jun 2013
Revisiting Natural Gradient for Deep Networks Razvan Pascanu Yoshua Bengio ODL 111 388 0 16 Jan 2013