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awesome-deep-phenomena
A curated list of papers of interesting empirical study and insight on deep learning. Continually updating...
https://github.com/MinghuiChen43/awesome-deep-phenomena
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- [paper - of-stability)
- [paper - Pretrained-ResNet-PyTorch)
- [paper - research/understanding-curricula)
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- [paper - of-Complexity-Measures-for-Deep-Learning-Generalization-in-Medical-Image-Analysis)
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- [paper - MAML)
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- [paper - lab/early_stopping_double_descent)
- [paper - descent-paper)
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- [paper - BiasVariance-Tradeoff)
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- [paper - Group/SMC-Bench)
- [paper - Deep-Neural-Networks-from-a-Sparsity-Perspective)
- [paper - tse/why-the-state-of-pruning-so-confusing)
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- [paper - EIC/SuperTickets)
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- [paper - lab/degrees-of-freedom)
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- [paper - Group/PrAC-LTH)
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- [paper - Time-Over-Parameterization)
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- [paper - lab/Synaptic-Flow)
- [paper - basel/neural-tangent-transfer)
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- [paper - ticket/rewinding-iclr20-public)
- [paper - Pruning-Greedy-Forward-Selection)
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- [paper - EIC/Early-Bird-Tickets)
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- [paper - research/deconstructing-lottery-tickets)
- [paper - ashuha/variational-dropout-sparsifies-dnn)
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- [paper - research/lottery-ticket-hypothesis)
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- [paper - pcn)
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- [paper - lab/robustness-development)
- [paper - robust-periphery)
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- [paper - ImageNet)
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- recent theoretical work - Ziv and Tishby on explaining the generalization ability of deep networks. The paper gives counter-examples that suggest aspects of the theory might not be relevant for all neural networks.
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- Previous work - Plane visualization of DNNs.
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- [paper - ch/equiv-nn-svm)
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- [paper - simon/shallow-learning)
- [paper - group/kernel-ood-generalization)
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- [paper - and-MF-examples)\
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- [paper - he/bayesian-ntk)
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- [paper - inductivebiasesharmlessinterpolation)
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- [paper - sparse-regularization)
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- [paper - zhuang/TorchDiffEqPack)
- [paper - research/OOD-failures)
- [paper - Lab-Berkeley/ReduNet)
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- [paper - kidger/NeuralCDE)
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- [paper - research/tree/master/dissecting-neural-odes)
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- [paper - field-fcdnn)
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- [paper - neural-odes)
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- [paper - 3-030-40245-7)
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- [paper - training-CNN)
- [paper - andr/relu_networks_overconfident)
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- [paper - as-gps/convnets-as-gps)
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- [paper - research/mean-field-cnns)
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- [paper - parametrization)
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- [paper - lab/deepchaos)
- Off the Convex Path Blog
- Francis Bach: Machine Learning Research Blog
- John Langford: Machine Learning (Theory) Blog
- Awesome Information Bottleneck Paper List - DEEP/Awesome-Information-Bottleneck) ![ ](https://img.shields.io/github/last-commit/ZIYU-DEEP/Awesome-Information-Bottleneck)
- Neural Tangent Kernel Papers - Papers) ![ ](https://img.shields.io/github/last-commit/kwignb/NeuralTangentKernel-Papers)
- Awesome Feature Learning in Deep Learning Theory - Feature-Learning-in-Deep-Learning-Thoery) ![ ](https://img.shields.io/github/last-commit/WeiHuang05/Awesome-Feature-Learning-in-Deep-Learning-Thoery)
- Awesome Trustworthy Deep Learning - trustworthy-deep-learning) ![ ](https://img.shields.io/github/last-commit/MinghuiChen43/awesome-trustworthy-deep-learning)
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Keywords
deep-learning
2
awesome-list
1
deep-neural-networks
1
deep-reinforcement-learning
1
information
1
information-bottleneck
1
adversarial-machine-learning
1
ai-alignment
1
backdoor
1
causality
1
fairness
1
gradient-leakage
1
green-ai
1
hallucinations
1
interpretable-deep-learning
1
machine-unlearning
1
membership-inference-attack
1
out-of-distribution-generalization
1
ownership
1
poisoning
1
privacy
1
robustness
1
security
1
uncertainty
1
watermarking
1