Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-14T10:58:29.041992Z
Paper Citation Record · LEDGER
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning
As of 19 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:1908.10059.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
51 of 51 outbound references displayed
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- verified fuzzy38
- unresolved12
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation f98a3161-940c-437c-a71e-3b33233182b3 · outbound
This paper cites Is object localization for free? - weakly-supervised learning with convolutional neural networks,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Is object localization for free? - weakly-supervised learning with convolutional neural networks,
Reference 1
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation fea526a3-b9fa-4bf7-bbbf-7f28b7e3c9a5 · outbound
This paper cites WILDCAT: weakly supervised learning of deep convnets for image classification, pointwise localization and segmentation,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning WILDCAT: weakly supervised learning of deep convnets for image classification, pointwise localization and segmentation,
Reference 2
- Resolution
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Source-reported events for the cited work
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Observation 3fc2e577-d981-48b5-b984-a16e64bc4fd1 · outbound
This paper cites Virtual adversarial training: a regularization method for supervised and semi-supervised learning,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Virtual adversarial training: a regularization method for supervised and semi-supervised learning,
Reference 3
- Resolution
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Source-reported events for the cited work
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Observation 6603088f-a410-4772-b68a-470ced2b0215 · outbound
This paper cites Mean teachers are better role mod- els: Weight-averaged consistency targets improve semi-supervised deep learning results,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Mean teachers are better role mod- els: Weight-averaged consistency targets improve semi-supervised deep learning results,
Reference 4
- Resolution
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Source-reported events for the cited work
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Observation f758659b-5439-412a-8645-058e923a69f3 · outbound
This paper cites Intriguing properties of neural networks.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Intriguing properties of neural networks
Reference 5
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Source-reported events for the cited work
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Observation f060f4a7-7606-4927-80ee-fb6814385431 · outbound
This paper cites Shake-shake regularization of 3-branch residual networks,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Shake-shake regularization of 3-branch residual networks,
Reference 6
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 0b421099-8faa-454d-b16f-3f38ac027a70 · outbound
This paper cites Dropout: a simple way to prevent neural networks from overfitting,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Dropout: a simple way to prevent neural networks from overfitting,
Reference 7
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 8569c9ca-68e7-4651-b8cb-c320c7730e55 · outbound
This paper cites Imagenet classification with deep convolutional neural networks,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Imagenet classification with deep convolutional neural networks,
Reference 8
- Resolution
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Source-reported events for the cited work
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Observation 437da6f2-0120-444b-a5db-875453192a86 · outbound
This paper cites mixup: Beyond Empirical Risk Minimization.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning mixup: Beyond Empirical Risk Minimization
Reference 9
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a5e1bd9e-91b8-432e-a5d5-c711e6c49feb · outbound
This paper cites MixUp as Locally Linear Out-Of-Manifold Regularization.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning MixUp as Locally Linear Out-Of-Manifold Regularization
Reference 10
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 5ce1439c-2f0f-4350-8c12-b106a9c9ac0b · outbound
This paper cites Model-agnostic meta-learning for fast adaptation of deep networks,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Model-agnostic meta-learning for fast adaptation of deep networks,
Reference 11
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 5b0ea480-18da-4f9b-b958-2baa34d479c8 · outbound
This paper cites Practical bayesian optimiza- tion of machine learning algorithms,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Practical bayesian optimiza- tion of machine learning algorithms,
Reference 12
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 2ea0d9ff-f06f-4c16-a595-9fb722d3c0ca · outbound
This paper cites Meta-Learning Update Rules for Unsupervised Representation Learning.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Meta-Learning Update Rules for Unsupervised Representation Learning
Reference 13
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9198931c-0b06-4fef-a419-f6958590dda1 · outbound
This paper cites Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks,
Reference 14
- Resolution
- verified fuzzy
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Source-reported events for the cited work
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Observation 9479f757-37a3-47cd-b196-2becb487f8f0 · outbound
This paper cites MixMatch: A Holistic Approach to Semi-Supervised Learning.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning MixMatch: A Holistic Approach to Semi-Supervised Learning
Reference 15
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7132935a-3381-4c6c-b823-47ab50724eb7 · outbound
This paper cites Keeping the neural networks simple by minimizing the description length of the weights,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Keeping the neural networks simple by minimizing the description length of the weights,
Reference 16
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 5dd3e196-dcf4-44b2-98ef-32a316047903 · outbound
This paper cites Adam: A method for stochastic optimiza- tion,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Adam: A method for stochastic optimiza- tion,
Reference 17
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 45f01717-9b41-4119-a6a8-c19748769c20 · outbound
This paper cites Deep residual learning for image recognition,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Deep residual learning for image recognition,
Reference 18
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9c9d2cd9-5a7e-43f3-88fc-a57b7fbd24dc · outbound
This paper cites AutoAugment: Learning Augmentation Policies from Data.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning AutoAugment: Learning Augmentation Policies from Data
Reference 19
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c0f0cf8c-fc04-48e0-b5ed-97091e4e9383 · outbound
This paper cites Between-class learning for image classification,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Between-class learning for image classification,
Reference 20
- Resolution
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Source-reported events for the cited work
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Observation 965a8d14-5239-4b97-abc5-18c67fe82eb3 · outbound
This paper cites Manifold Mixup: Better Representations by Interpolating Hidden States.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Manifold Mixup: Better Representations by Interpolating Hidden States
Reference 21
- Resolution
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Source-reported events for the cited work
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Observation b4b974e7-b022-46a0-85d8-24498057b466 · outbound
This paper cites Learning to learn: Introduction and overview,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Learning to learn: Introduction and overview,
Reference 22
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 750c5a91-026e-4929-b61c-a746f7b7b66d · outbound
This paper cites Bengio, S.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Bengio, S
Reference 23
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation c7f4c976-ffd9-4315-b6a1-f5b557679670 · outbound
This paper cites Optimization as a model for few-shot learning,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Optimization as a model for few-shot learning,
Reference 24
- Resolution
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Source-reported events for the cited work
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Observation 939dd341-8770-4b44-8d96-9d0105c10f4f · outbound
This paper cites Prototypical networks for few- shot learning,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Prototypical networks for few- shot learning,
Reference 25
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation ece9e0df-813c-48f6-84a8-5b6565ab0d4d · outbound
This paper cites A simple neural attentive meta-learner,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning A simple neural attentive meta-learner,
Reference 26
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 5532fd0a-9533-40ae-912e-9d42dad893c7 · outbound
This paper cites Rapid adapta- tion with conditionally shifted neurons,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Rapid adapta- tion with conditionally shifted neurons,
Reference 27
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation ff5dc695-6b17-411c-ae58-8267844ca3ee · outbound
This paper cites Approximate least trimmed sum of squares fitting and applications in image analysis,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Approximate least trimmed sum of squares fitting and applications in image analysis,
Reference 28
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 418615d3-319f-41e0-9758-eee49c82f1ec · outbound
This paper cites Deep asymmetric pairwise hashing,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Deep asymmetric pairwise hashing,
Reference 29
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 443497f1-247f-4feb-b4d9-750aec9b1e2e · outbound
This paper cites Supervised discrete hashing,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Supervised discrete hashing,
Reference 30
- Resolution
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Source-reported events for the cited work
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Observation f3691a7d-2778-4bea-8c71-1d1441a30ca1 · outbound
This paper cites Learning to reweight examples for robust deep learning,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Learning to reweight examples for robust deep learning,
Reference 31
- Resolution
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Source-reported events for the cited work
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Observation 88c3d180-e4d4-4bb7-88f4-f2ff107328cc · outbound
This paper cites Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vi- sion architectures,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vi- sion architectures,
Reference 32
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Source-reported events for the cited work
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Observation 13782d1d-ad06-4904-abe2-9162c337f4e0 · outbound
This paper cites Auto-weka: combined selection and hyperparameter optimization of classification algorithms,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Auto-weka: combined selection and hyperparameter optimization of classification algorithms,
Reference 33
- Resolution
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Source-reported events for the cited work
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Observation 6ab55e35-f244-4d72-a734-c553c7b22bef · outbound
This paper cites Practical bayesian optimiza- tion of machine learning algorithms,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Practical bayesian optimiza- tion of machine learning algorithms,
Reference 34
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 91f9a4e8-d0f9-4587-be10-36e7209a346c · outbound
This paper cites Hyperparameter optimization with approximate gradient,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Hyperparameter optimization with approximate gradient,
Reference 35
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 52df3d9a-631b-481c-b3dc-b8db1a561579 · outbound
This paper cites Temporal Ensembling for Semi-Supervised Learning.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Temporal Ensembling for Semi-Supervised Learning
Reference 36
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Observation 9f90092c-5572-4c72-b875-0075d7436dca · outbound
This paper cites Learning classification with unlabeled data,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Learning classification with unlabeled data,
Reference 37
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 7bd3fd64-967a-4a5f-962f-e68be430e25c · outbound
This paper cites Asymmetric tri-training for unsu- pervised domain adaptation,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Asymmetric tri-training for unsu- pervised domain adaptation,
Reference 38
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 39b5c0d1-c10c-49aa-af01-50c35ceb62aa · outbound
This paper cites Learning semantic rep- resentations for unsupervised domain adaptation,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Learning semantic rep- resentations for unsupervised domain adaptation,
Reference 39
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 2fb91b3a-d0ab-406c-8afe-768b3c14dba7 · outbound
This paper cites Parseval networks: Improving robustness to adversarial examples,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Parseval networks: Improving robustness to adversarial examples,
Reference 40
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation c1122c88-8349-4059-ba27-ae2330c4801e · outbound
This paper cites Lipschitz-margin training: Scal- able certification of perturbation invariance for deep neural networks,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Lipschitz-margin training: Scal- able certification of perturbation invariance for deep neural networks,
Reference 41
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation fccd8b9c-46ff-44df-9d20-c0ee31c5e976 · outbound
This paper cites Progressive neural architecture search,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Progressive neural architecture search,
Reference 42
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 22b6038b-8faa-48a8-bc1f-83bbf40ce6d7 · outbound
This paper cites An overview of bilevel opti- mization,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning An overview of bilevel opti- mization,
Reference 43
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 44de3394-75b4-4ae7-8b3b-2da66c2ad57c · outbound
This paper cites Scalable gradient- based tuning of continuous regularization hyperparameters,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Scalable gradient- based tuning of continuous regularization hyperparameters,
Reference 44
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation ad01e51a-0579-4051-9777-46a0be8c08ae · outbound
This paper cites Realistic evaluation of deep semi-supervised learning algorithms,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Realistic evaluation of deep semi-supervised learning algorithms,
Reference 45
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation ba9ceed7-00b2-461d-8fee-682681db95e4 · outbound
This paper cites Reading digits in natural images with unsupervised feature learning,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Reading digits in natural images with unsupervised feature learning,
Reference 46
- Resolution
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Source-reported events for the cited work
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Observation 816b7479-7971-446d-921a-c1e2efc2a773 · outbound
This paper cites Imagenet large scale visual recognition challenge,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Imagenet large scale visual recognition challenge,
Reference 47
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 203f37f4-52e9-46a5-9113-dd5f7553c91e · outbound
This paper cites Identity mappings in deep residual networks,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Identity mappings in deep residual networks,
Reference 48
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation c8ab7880-e703-426d-9948-bc7ee0922502 · outbound
This paper cites SGDR: stochastic gradient descent with warm restarts,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning SGDR: stochastic gradient descent with warm restarts,
Reference 49
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a083a984-4025-4e42-845d-220026366857 · outbound
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MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Wide residual networks,
Reference 50
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation af6f0e90-337b-45de-b55c-b92d41333d45 · outbound
This paper cites Self-ensembling for visual domain adaptation,.
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Self-ensembling for visual domain adaptation,
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T10:58:29.200343Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Pith citing papers
No inbound Pith citation observations are available.