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Collections including paper arxiv:1512.03385

Back to Basics: Let Denoising Generative Models Denoise

Paper • 2511.13720 • Published Nov 17, 2025 • 67
Deep Residual Learning for Image Recognition

Paper • 1512.03385 • Published Dec 10, 2015 • 12
mHC: Manifold-Constrained Hyper-Connections

Paper • 2512.24880 • Published 8 days ago • 227

High Low Media's AI/ML bookshelf

Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

Paper • 1502.01852 • Published Feb 6, 2015 • 1
Deep Residual Learning for Image Recognition

Paper • 1512.03385 • Published Dec 10, 2015 • 12
Focal Loss for Dense Object Detection

Paper • 1708.02002 • Published Aug 7, 2017
Scaling Proprioceptive-Visual Learning with Heterogeneous Pre-trained Transformers

Paper • 2409.20537 • Published Sep 30, 2024 • 13

Ilya 30u30 (Partial)

A selection of papers recommended by Ilya Sutskever to be up-to-speed on the bleeding edge in AI (at least the ones with ArXiv links).

Recurrent Neural Network Regularization

Paper • 1409.2329 • Published Sep 8, 2014 • 1
Pointer Networks

Paper • 1506.03134 • Published Jun 9, 2015 • 1
Order Matters: Sequence to sequence for sets

Paper • 1511.06391 • Published Nov 19, 2015 • 1
GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism

Paper • 1811.06965 • Published Nov 16, 2018 • 1

Ilya's papers for Carmack

Ilya Sutskever: "If you really learn all of these, you’ll know 90% of what matters today." Full list: https://punkx.org/jackdoe/30.html

Recurrent Neural Network Regularization

Paper • 1409.2329 • Published Sep 8, 2014 • 1
Pointer Networks

Paper • 1506.03134 • Published Jun 9, 2015 • 1
Order Matters: Sequence to sequence for sets

Paper • 1511.06391 • Published Nov 19, 2015 • 1
GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism

Paper • 1811.06965 • Published Nov 16, 2018 • 1

Papers - Custom Layers - No Dropout - Batch Normalization

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Paper • 1502.03167 • Published Feb 11, 2015 • 2
Deep Residual Learning for Image Recognition

Paper • 1512.03385 • Published Dec 10, 2015 • 12

Image Models - Essential Research Papers

ylecun/mnist

Viewer • Updated Aug 8, 2024 • 70k • 78.8k • 219
uoft-cs/cifar10

Viewer • Updated Jan 4, 2024 • 60k • 90.7k • 95
CINIC-10 is not ImageNet or CIFAR-10

Paper • 1810.03505 • Published Oct 2, 2018
ImageNet Large Scale Visual Recognition Challenge

Paper • 1409.0575 • Published Sep 1, 2014 • 9

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Paper • 1810.04805 • Published Oct 11, 2018 • 25
Deep Residual Learning for Image Recognition

Paper • 1512.03385 • Published Dec 10, 2015 • 12

Computer Vision papers 👓

Rich feature hierarchies for accurate object detection and semantic segmentation

Paper • 1311.2524 • Published Nov 11, 2013 • 1
DeepPose: Human Pose Estimation via Deep Neural Networks

Paper • 1312.4659 • Published Dec 17, 2013 • 1
Generative Adversarial Networks

Paper • 1406.2661 • Published Jun 10, 2014 • 5
scikit-image: Image processing in Python

Paper • 1407.6245 • Published Jul 23, 2014 • 1

Papers - Image - Training - Per-class Regressor (PCR)

Deep Residual Learning for Image Recognition

Paper • 1512.03385 • Published Dec 10, 2015 • 12

Papers - Image - Datasets - ImageNet

All you need is a good init

Paper • 1511.06422 • Published Nov 19, 2015 • 1
Align Your Steps: Optimizing Sampling Schedules in Diffusion Models

Paper • 2404.14507 • Published Apr 22, 2024 • 23
Efficient Transformer Encoders for Mask2Former-style models

Paper • 2404.15244 • Published Apr 23, 2024 • 1
Deep Residual Learning for Image Recognition

Paper • 1512.03385 • Published Dec 10, 2015 • 12

Back to Basics: Let Denoising Generative Models Denoise

Paper • 2511.13720 • Published Nov 17, 2025 • 67
Deep Residual Learning for Image Recognition

Paper • 1512.03385 • Published Dec 10, 2015 • 12
mHC: Manifold-Constrained Hyper-Connections

Paper • 2512.24880 • Published 8 days ago • 227

Image Models - Essential Research Papers

ylecun/mnist

Viewer • Updated Aug 8, 2024 • 70k • 78.8k • 219
uoft-cs/cifar10

Viewer • Updated Jan 4, 2024 • 60k • 90.7k • 95
CINIC-10 is not ImageNet or CIFAR-10

Paper • 1810.03505 • Published Oct 2, 2018
ImageNet Large Scale Visual Recognition Challenge

Paper • 1409.0575 • Published Sep 1, 2014 • 9

High Low Media's AI/ML bookshelf

Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

Paper • 1502.01852 • Published Feb 6, 2015 • 1
Deep Residual Learning for Image Recognition

Paper • 1512.03385 • Published Dec 10, 2015 • 12
Focal Loss for Dense Object Detection

Paper • 1708.02002 • Published Aug 7, 2017
Scaling Proprioceptive-Visual Learning with Heterogeneous Pre-trained Transformers

Paper • 2409.20537 • Published Sep 30, 2024 • 13

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Paper • 1810.04805 • Published Oct 11, 2018 • 25
Deep Residual Learning for Image Recognition

Paper • 1512.03385 • Published Dec 10, 2015 • 12

Ilya 30u30 (Partial)

A selection of papers recommended by Ilya Sutskever to be up-to-speed on the bleeding edge in AI (at least the ones with ArXiv links).

Recurrent Neural Network Regularization

Paper • 1409.2329 • Published Sep 8, 2014 • 1
Pointer Networks

Paper • 1506.03134 • Published Jun 9, 2015 • 1
Order Matters: Sequence to sequence for sets

Paper • 1511.06391 • Published Nov 19, 2015 • 1
GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism

Paper • 1811.06965 • Published Nov 16, 2018 • 1

Computer Vision papers 👓

Rich feature hierarchies for accurate object detection and semantic segmentation

Paper • 1311.2524 • Published Nov 11, 2013 • 1
DeepPose: Human Pose Estimation via Deep Neural Networks

Paper • 1312.4659 • Published Dec 17, 2013 • 1
Generative Adversarial Networks

Paper • 1406.2661 • Published Jun 10, 2014 • 5
scikit-image: Image processing in Python

Paper • 1407.6245 • Published Jul 23, 2014 • 1

Ilya's papers for Carmack

Ilya Sutskever: "If you really learn all of these, you’ll know 90% of what matters today." Full list: https://punkx.org/jackdoe/30.html

Recurrent Neural Network Regularization

Paper • 1409.2329 • Published Sep 8, 2014 • 1
Pointer Networks

Paper • 1506.03134 • Published Jun 9, 2015 • 1
Order Matters: Sequence to sequence for sets

Paper • 1511.06391 • Published Nov 19, 2015 • 1
GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism

Paper • 1811.06965 • Published Nov 16, 2018 • 1

Papers - Image - Training - Per-class Regressor (PCR)

Deep Residual Learning for Image Recognition

Paper • 1512.03385 • Published Dec 10, 2015 • 12

Papers - Custom Layers - No Dropout - Batch Normalization

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Paper • 1502.03167 • Published Feb 11, 2015 • 2
Deep Residual Learning for Image Recognition

Paper • 1512.03385 • Published Dec 10, 2015 • 12

Papers - Image - Datasets - ImageNet

All you need is a good init

Paper • 1511.06422 • Published Nov 19, 2015 • 1
Align Your Steps: Optimizing Sampling Schedules in Diffusion Models

Paper • 2404.14507 • Published Apr 22, 2024 • 23
Efficient Transformer Encoders for Mask2Former-style models

Paper • 2404.15244 • Published Apr 23, 2024 • 1
Deep Residual Learning for Image Recognition

Paper • 1512.03385 • Published Dec 10, 2015 • 12

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