Methods › General › Meta-Learning Algorithms › MAML › Papers, page 3

Model-Agnostic Meta-Learning

MAML

Papers archive 2025-07-28

archive papers tagged: 232 · with a code link: 90 · where Syntology ran a sample: 28 (18 with a run with no instrument failure, 10 where every run was a failure of Syntology's instrument) Syntology

Show: all tagged papersonly where code ran (28 of 232 tagged: 18 with a run with no instrument failure, 10 where every run was a failure of Syntology's instrument)

Page 3 of 3: papers 201 to 232 of 232, newest first by the archive's date (ties by slug), in archive order.

Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code, as “N ran (of which C constructed an object rather than computing a result; K with no instrument failure: H honoured, V violated, P with no contract checked; I where Syntology's instrument failed) · U unverified”; the instrument figure counts failures of Syntology's instrument, not of the code. It is per sample and not a correctness claim. When the archive marks a repository official for the paper, the line starts with that repository's state (the archive's flag, not a verdict on who wrote the code; “community repositories only” when every sample that ran came from a community repository, “official: no sample here; runs from other or unrecorded repositories” when some came from a repository the paper names or has in its text, or from none recorded); hover it for the repositories the samples that ran came from.

• ES-MAML: Simple Hessian-Free Meta Learning
  25 Sep 2019 · 1 repository · arXiv:1910.01215
• Coupled Generative Adversarial Network for Continuous Fine-grained Action Segmentation
  20 Sep 2019 · 0 repositories · arXiv:1909.09283
• Fine-grained Action Segmentation using the Semi-Supervised Action GAN
  20 Sep 2019 · 0 repositories · arXiv:1909.09269
• Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML
  19 Sep 2019 · 2 repositories · arXiv:1909.09157
• Modular Meta-Learning with Shrinkage
  12 Sep 2019 · 0 repositories · arXiv:1909.05557
• Meta-Learning with Implicit Gradients
  10 Sep 2019 · 6 repositories · arXiv:1909.04630
  Syntology official (archive's flag): 7 ran · 27 ran (of which 4 constructed an object rather than computing a result; 8 with no instrument failure: 3 honoured, 1 violated, 4 with no contract checked; 19 where Syntology's instrument failed) · 9 unverified (of 36 harvested samples) · 10 pointer-only (licence)
• On the Convergence Theory of Gradient-Based Model-Agnostic Meta-Learning Algorithms
  27 Aug 2019 · 0 repositories · arXiv:1908.10400
• Meta Reasoning over Knowledge Graphs
  13 Aug 2019 · 0 repositories · arXiv:1908.04877
• Towards Understanding Generalization in Gradient-Based Meta-Learning
  16 Jul 2019 · 0 repositories · arXiv:1907.07287
• Evolvability ES: Scalable and Direct Optimization of Evolvability
  13 Jul 2019 · 1 repository · arXiv:1907.06077
• A Model-based Approach for Sample-efficient Multi-task Reinforcement Learning
  11 Jul 2019 · 0 repositories · arXiv:1907.04964
• Evolutionary Reinforcement Learning for Sample-Efficient Multiagent Coordination
  18 Jun 2019 · 0 repositories · arXiv:1906.07315
• Alpha MAML: Adaptive Model-Agnostic Meta-Learning
  17 May 2019 · 0 repositories · arXiv:1905.07435
• Follow the Attention: Combining Partial Pose and Object Motion for Fine-Grained Action Detection
  11 May 2019 · 0 repositories · arXiv:1905.04430
• Attentive Task-Agnostic Meta-Learning for Few-Shot Text Classification
  1 May 2019 · 0 repositories
• NoRML: No-Reward Meta Learning
  4 Mar 2019 · 1 repository · arXiv:1903.01063
• Online Meta-Learning
  22 Feb 2019 · 0 repositories · arXiv:1902.08438
• Learning to Generalize from Sparse and Underspecified Rewards
  19 Feb 2019 · 1 repository · arXiv:1902.07198
• Meta-Curvature
  9 Feb 2019 · 1 repository · arXiv:1902.03356
• An Investigation of Few-Shot Learning in Spoken Term Classification
  26 Dec 2018 · 1 repository · arXiv:1812.10233
• Toward Multimodal Model-Agnostic Meta-Learning
  18 Dec 2018 · 0 repositories · arXiv:1812.07172
• The effects of negative adaptation in Model-Agnostic Meta-Learning
  5 Dec 2018 · 0 repositories · arXiv:1812.02159
• How to train your MAML
  22 Oct 2018 · 10 repositories · arXiv:1810.09502
  Syntology 1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified (of 1 harvested sample) · 1 pointer-only (licence)
• Gradient Agreement as an Optimization Objective for Meta-Learning
  18 Oct 2018 · 0 repositories · arXiv:1810.08178
• Fast Context Adaptation via Meta-Learning
  8 Oct 2018 · 1 repository · arXiv:1810.03642
  Syntology official (archive's flag): 4 ran · 4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified (of 6 harvested samples) · 1 pointer-only (licence)
• Meta-Learning by the Baldwin Effect
  6 Jun 2018 · 0 repositories · arXiv:1806.07917
• On the Importance of Attention in Meta-Learning for Few-Shot Text Classification
  3 Jun 2018 · 0 repositories · arXiv:1806.00852
• On First-Order Meta-Learning Algorithms
  8 Mar 2018 · 13 repositories · arXiv:1803.02999
  Syntology official (archive's flag): 8 ran · 27 ran (of which 2 constructed an object rather than computing a result; 9 with no instrument failure: 1 honoured, 2 violated, 6 with no contract checked; 18 where Syntology's instrument failed) · 15 unverified (of 42 harvested samples) · 13 pointer-only (licence)
• Deep Meta-Learning: Learning to Learn in the Concept Space
  10 Feb 2018 · 0 repositories · arXiv:1802.03596
• Recasting Gradient-Based Meta-Learning as Hierarchical Bayes
  26 Jan 2018 · 0 repositories · arXiv:1801.08930
• Meta-SGD: Learning to Learn Quickly for Few-Shot Learning
  31 Jul 2017 · 9 repositories · arXiv:1707.09835
• Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
  9 Mar 2017 · 85 repositories · arXiv:1703.03400
  Syntology official (archive's flag): 1 ran · 103 ran (of which 35 constructed an object rather than computing a result; 72 with no instrument failure: 6 honoured, 1 violated, 65 with no contract checked; 31 where Syntology's instrument failed) · 51 unverified (of 154 harvested samples) · 57 pointer-only (licence)