Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures | Paper Citation Record

Observation 383ae0cd-83ed-4842-a36e-4433b5ac2b9e · outbound

This paper cites Structural interplay between germline interactions and adaptive recognition deter- mines the bandwidth of tcr-peptide-mhc cross-reactivity.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Structural interplay between germline interactions and adaptive recognition deter- mines the bandwidth of tcr-peptide-mhc cross-reactivity

Reference 1

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Unresolved cited work

Reference 2

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This paper cites Efficient 3d deep learning model for medical image semantic segmentation.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Efficient 3d deep learning model for medical image semantic segmentation

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This paper cites Flamingo: a visual language model for few-shot learning.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Flamingo: a visual language model for few-shot learning

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This paper cites Deep speech 2: End-to-end speech recognition in english and mandarin.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Deep speech 2: End-to-end speech recognition in english and mandarin

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This paper cites Hoffman, David Pfau, Tom Schaul, and Nando de Freitas.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Hoffman, David Pfau, Tom Schaul, and Nando de Freitas

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This paper cites Defining Benchmarks for Continual Few-Shot Learning.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Defining Benchmarks for Continual Few-Shot Learning

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This paper cites On the texture bias for few-shot cnn segmentation.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures On the texture bias for few-shot cnn segmentation

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This paper cites Hyperfields: Towards zero-shot generation of nerfs from text, 2023.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Hyperfields: Towards zero-shot generation of nerfs from text, 2023

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Observation 12c4c17f-9a34-4ac4-842e-a925d5bb7edc · outbound

This paper cites Hypernetwork designs for improved classification and robust meta-learning, 2020.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Hypernetwork designs for improved classification and robust meta-learning, 2020

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This paper cites Online meta-learning via learning with layer-distributed memory.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Online meta-learning via learning with layer-distributed memory

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This paper cites Meta-DRN: Meta-Learning for 1-Shot Image Segmentation.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Meta-DRN: Meta-Learning for 1-Shot Image Segmentation

Reference 12

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Observation 0d429219-fc6e-4e4b-8c78-f075852cbfa2 · outbound

This paper cites Pixelnet: Representation of the pixels, by the pixels, and for the pixels, 2017.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Pixelnet: Representation of the pixels, by the pixels, and for the pixels, 2017

Reference 13

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This paper cites Mip-nerf: A multiscale representation for anti-aliasing neural radiance fields.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Mip-nerf: A multiscale representation for anti-aliasing neural radiance fields

Reference 14

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Mip- nerf 360: Unbounded anti-aliased neural radiance fields

Reference 15

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This paper cites Rae, Simon Osindero, and Timothy P.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Rae, Simon Osindero, and Timothy P

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This paper cites Stanley, Jeff Clune, and Nick Cheney.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Stanley, Jeff Clune, and Nick Cheney

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This paper cites On the optimization of a synaptic learning rule.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures On the optimization of a synaptic learning rule

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This paper cites Practical recommendations for gradient-based training of deep architectures.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Practical recommendations for gradient-based training of deep architectures

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This paper cites Henriques, Philip H.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Henriques, Philip H

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This paper cites Stylegan knows normal, depth, albedo, and more.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Stylegan knows normal, depth, albedo, and more

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This paper cites Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning

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This paper cites Unsupervised learning of visual features by contrasting cluster assignments.Advances in neural information processing systems, 33:9912–9924, 2020.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Unsupervised learning of visual features by contrasting cluster assignments.Advances in neural information processing systems, 33:9912–9924, 2020

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This paper cites Deep local shapes: Learning local sdf priors for detailed 3d reconstruction.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Deep local shapes: Learning local sdf priors for detailed 3d reconstruction

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This paper cites Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, Jianxiong Xiao, Li Yi, and Fisher Yu.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, Jianxiong Xiao, Li Yi, and Fisher Yu

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Principled weight initialization for hyper- networks

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Tensorf: Tensorial radiance fields, 2022

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Fantasia3d: Disentangling geometry and appearance for high-quality text-to-3d content creation, 2023

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This paper cites A simple frame- work for contrastive learning of visual representations.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures A simple frame- work for contrastive learning of visual representations

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This paper cites A Closer Look at Few-shot Classification.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures A Closer Look at Few-shot Classification

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Improved Baselines with Momentum Contrastive Learning

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Dynamic convolution: Attention over convolution kernels

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Stylizing 3d scene via implicit representation and hypernetwork, 2021

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Chemberta: Large-scale self-supervised pretraining for molecular property prediction, 2020

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures 3d u-net: learning dense volumetric segmentation from sparse annotation

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This paper cites T-cell antigen receptor genes and t-cell recognition.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures T-cell antigen receptor genes and t-cell recognition

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Imagenet: A large- scale hierarchical image database

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Imagenet: A large- scale hierarchical image database

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Improved Regularization of Convolutional Neural Networks with Cutout

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Diffusion models beat gans on image synthesis

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Unsupervised visual representation learning by context prediction

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Machine learning methods for small data challenges in molecular science

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Hyperdiffu- sion: Generating implicit neural fields with weight-space diffusion

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Kiloneus: A versatile neural implicit surface representation for real-time rendering, 2022

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Model-agnostic meta-learning for fast adaptation of deep networks

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Kakade, and Sergey Levine

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Nerf: Neural radiance field in 3d vision, a comprehensive review, 2022

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Fast r-cnn

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Evolving modular fast-weight networks for control

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Neural Turing Machines

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Development or dreamfield delusions: Assessing casino gambling’s costs and benefits

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Snapnet-r: Consistent 3d multi-view semantic labeling for robotics

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures An investigation of model-free planning

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Spottune: transfer learning through adaptive fine-tuning

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures HyperNetworks

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Unresolved cited work

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Masked autoencoders are scalable vision learners

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This paper cites Momentum Contrast for Unsupervised Visual Representation Learning.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Momentum Contrast for Unsupervised Visual Representation Learning

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Observation 6b3b12ce-9249-4e5d-b0c2-6266a1b6fb99 · outbound

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Mask r-cnn

Reference 61

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Observation b5eae914-d85b-4954-80d8-466d98b75990 · outbound

This paper cites Deep residual learning for image recognition.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Deep residual learning for image recognition

Reference 62

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Observation 56fa57f6-ff03-4c98-b863-1af1746663e8 · outbound

This paper cites Deep residual learning for image recognition.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Deep residual learning for image recognition

Reference 63

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Observation fcfb74f5-afa6-427c-b08b-fdb06a1fec1c · outbound

This paper cites On the Effectiveness of Adapter-based Tuning for Pretrained Language Model Adaptation.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures On the Effectiveness of Adapter-based Tuning for Pretrained Language Model Adaptation

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Observation 0a95f90f-aa28-47ce-a1b4-d9e903434f63 · outbound

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Denoising diffusion probabilistic models

Reference 65

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Observation 3815d854-e7e8-468e-bd69-5f8330a9d49b · outbound

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Long short-term memory

Reference 66

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Observation 8e23f21b-19de-4900-8643-7a8674c753ac · outbound

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Learning to learn using gradient descent

Reference 67

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Observation 8868e35f-edee-4477-a088-b5e6a0526cd8 · outbound

This paper cites Avatarclip: Zero-shot text-driven generation and animation of 3d avatars.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Avatarclip: Zero-shot text-driven generation and animation of 3d avatars

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Observation af796a3b-8c71-414c-b493-f2dffa307f6b · outbound

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Equivariant diffusion for molecule generation in 3d, 2022

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Observation 4da49965-3032-4721-adf3-258a5eacc9ff · outbound

This paper cites Meta-Learning in Neural Networks: A Survey.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Meta-Learning in Neural Networks: A Survey

Reference 70

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Observation 9f29867c-a415-4e45-b3a7-1bc8e85ed404 · outbound

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Universal Language Model Fine-tuning for Text Classification

Reference 71

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Observation 43d4f527-a493-46c0-98d9-aa1d89cf50bf · outbound

This paper cites Attention-based multi-context guiding for few-shot semantic segmentation.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Attention-based multi-context guiding for few-shot semantic segmentation

Reference 72

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Observation 355fe682-5a28-4b73-9d68-35710d6b2efe · outbound

This paper cites Supervoxel convolution for online 3d semantic segmentation.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Supervoxel convolution for online 3d semantic segmentation

Reference 73

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Observation c305831b-cb47-4ce0-9375-135a7bf7a30f · outbound

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Self-challenging improves cross-domain generalization

Reference 74

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Observation abf486d0-5987-40dd-9bb5-62e5fbf5de8a · outbound

This paper cites Can we predict t cell specificity with digital biology and machine learning? Nature Reviews Immunology, pages 1–11, 2023.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Can we predict t cell specificity with digital biology and machine learning? Nature Reviews Immunology, pages 1–11, 2023

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Observation 3316143d-b7b7-4256-8216-c7c51b8467f3 · outbound

This paper cites Averaging Weights Leads to Wider Optima and Better Generalization.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Averaging Weights Leads to Wider Optima and Better Generalization

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-06T19:32:54.226699Z

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Observation 8bb58740-6ad5-44b4-9c18-6df102815379 · outbound

This paper cites Barron, Pieter Abbeel, and Ben Poole.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Barron, Pieter Abbeel, and Ben Poole

Reference 77

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Observation c110fe16-4662-4a9c-b598-830876b5f60e · outbound

This paper cites Putting nerf on a diet: Semantically consistent few-shot view synthesis.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Putting nerf on a diet: Semantically consistent few-shot view synthesis

Reference 78

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Observation cd26108d-7f30-4652-8d51-f8d322cdd2b8 · outbound

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Meta-learning representations for continual learning

Reference 79

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Observation e4433f34-62f9-49f3-9c1d-0430880e7d9b · outbound

This paper cites Transfer learning from speaker verification to multispeaker text-to-speech synthesis.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Transfer learning from speaker verification to multispeaker text-to-speech synthesis

Reference 80

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Observation 984f4ace-2185-4bf8-a018-260c3b238663 · outbound

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Human learning and memory

Reference 81

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Observation f18b2814-4e33-42e7-a433-46cc50fd17b6 · outbound

This paper cites Shap-e: Generating conditional 3d implicit functions, 2023.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Shap-e: Generating conditional 3d implicit functions, 2023

Reference 82

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Observation 3d2492d6-ecd2-444b-aa4c-5891b62250bb · outbound

This paper cites Lerf: Language embedded radiance fields.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Lerf: Language embedded radiance fields

Reference 83

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Observation 218747ff-0a69-4014-b2f1-1231d20dc927 · outbound

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Kingma and Jimmy Ba

Reference 84

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Observation 21afddff-a95b-489c-8b04-0dfcddb9c584 · outbound

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Overcoming catastrophic forgetting in neural networks

Reference 85

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Observation ef54feef-ef75-4208-bffe-0ccc07a83b3a · outbound

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Meta Learning Backpropagation And Improving It

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Resolution: unresolved; no resolver link, observed 2026-08-06T19:32:54.259374Z

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Observation 688c9580-4a69-410f-bd9c-8a3181337ccf · outbound

This paper cites Decomposing nerf for editing via feature field distillation.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Decomposing nerf for editing via feature field distillation

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-06T19:32:54.262780Z

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Observation af0c06cf-5ef6-4c63-aa0a-a366e86baa33 · outbound

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Learning multiple layers of features from tiny images, 2009

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-06T19:32:54.265819Z

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Observation 2d4f7ea3-ce3b-40fc-8c9c-3e5ac977e205 · outbound

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Imagenet classification with deep convolutional neural networks

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-06T19:32:54.269154Z

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Observation 7163ac85-3641-4d81-b982-f18b728461ad · outbound

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Role of cognitive factors in the acquisition of cognitive skill

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-06T19:32:54.271587Z

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Observation 728ed3cd-e9e5-4d92-b615-0d11a0749160 · outbound

This paper cites Omniglot git repo, 2015.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Omniglot git repo, 2015

Reference 91

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Observation 998bb67d-7b26-4fba-83e7-2902b2692ee6 · outbound

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Human-level concept learning through probabilistic program induction

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-06T19:32:54.277516Z

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Observation 76d47ec9-39dc-40cd-8614-afb7b273807a · outbound

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Colorization as a proxy task for visual understanding

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-06T19:32:54.280031Z

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Observation 41fcc85a-18ab-4897-9510-e116c02f25a4 · outbound

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Deeper, broader and artier domain generalization

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-06T19:32:54.282290Z

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Observation 21910a93-84de-4411-957b-4c167d11ab6b · outbound

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Learning to generalize: Meta-learning for domain generalization

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-06T19:32:54.285462Z

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Observation 321c9587-ebb5-4c36-8206-9a56a1376bd4 · outbound

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Referring image segmentation via recurrent refinement networks

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-06T19:32:54.288973Z

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Observation c984569c-27e3-4600-92d5-48c4fd865127 · outbound

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Fss-1000: A 1000-class dataset for few-shot segmentation

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Resolution: unresolved; no resolver link, observed 2026-08-06T19:32:54.292212Z

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Observation 1f9d5112-b011-4abc-9af4-185bae7352fc · outbound

This paper cites Meta-SGD: Learning to Learn Quickly for Few-Shot Learning.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Meta-SGD: Learning to Learn Quickly for Few-Shot Learning

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Resolution: unresolved; no resolver link, observed 2026-08-06T19:32:54.294985Z

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Observation 17d79b07-9858-4366-b831-e452282ddebf · outbound

This paper cites Magic3D: High-Resolution Text-to-3D Content Creation.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Magic3D: High-Resolution Text-to-3D Content Creation

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-06T19:32:54.298796Z

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Observation 774da49e-0364-4e2a-ab42-3d27b9e1f9bd · outbound

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Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Lee, and Michael I

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-06T19:32:54.302737Z

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Observation 532c0dc8-8603-4ab7-a6ea-bdb4aae84ed1 · outbound

This paper cites Audio self-supervised learning: A survey.

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures Audio self-supervised learning: A survey

Reference 101

Resolution: unresolved; no resolver link, observed 2026-08-06T19:32:54.306268Z

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