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Generalization Bounds

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/chl8856/survite

공식 코드

SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data

https://github.com/csinva/imodels

공식 코드

Fast Interpretable Greedy-Tree Sums

https://github.com/cwein3/all-layer-margin-opt

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Improved Sample Complexities for Deep Networks and Robust Classification via an All-Layer Margin

https://github.com/dccsillag/experiments-causal-generalization-bounds

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Generalization Bounds for Causal Regression: Insights, Guarantees and Sensitivity Analysis

https://github.com/decodepfl/pac-snoc

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A PAC-Bayesian Framework for Optimal Control with Stability Guarantees

https://github.com/diarra2339/pac-bayes-wgan

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PAC-Bayesian Generalization Bounds for Adversarial Generative Models

https://github.com/dlr-rm/bpnn

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Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks

https://github.com/felipemaiapolo/infoselect

공식 코드

Effective Sample Size, Dimensionality, and Generalization in Covariate Shift Adaptation

https://github.com/fredrikhellstrom/comparing-comparators

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Comparing Comparators in Generalization Bounds

https://github.com/fshp971/RPG

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Robustness, Privacy, and Generalization of Adversarial Training

https://github.com/gletarte/dichotomize-and-generalize

공식 코드

Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks

https://github.com/gletarte/pbrff

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Pseudo-Bayesian Learning with Kernel Fourier Transform as Prior

https://github.com/graal-research/pick-to-learn

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Sample Compression Unleashed: New Generalization Bounds for Real Valued Losses

https://github.com/grasp-lyrl/sloppy

공식 코드

Does the Data Induce Capacity Control in Deep Learning?

https://github.com/gregorbachmann/leaveoneout

공식 코드

Generalization Through The Lens Of Leave-One-Out Error

https://github.com/guoji-fu/dignn

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Implicit Graph Neural Diffusion Networks: Convergence, Generalization, and Over-Smoothing

https://github.com/guoqiangwoodrowwu/macro-auc-theory

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Towards Understanding Generalization of Macro-AUC in Multi-label Learning

https://github.com/herianhe/generrorssl_2022

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Information-Theoretic Characterization of the Generalization Error for Iterative Semi-Supervised Learning

https://github.com/hirsch-lab/cyminiball

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Learning Non-Vacuous Generalization Bounds from Optimization

https://github.com/hong-xian/backdoor-attack

공식 코드

Generalization Bound and New Algorithm for Clean-Label Backdoor Attack

https://github.com/hrayrhar/f-cmi

공식 코드

Information-theoretic generalization bounds for black-box learning algorithms

https://github.com/hrayrhar/limit-label-memorization

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Improving Generalization by Controlling Label-Noise Information in Neural Network Weights

https://github.com/hzakerinia/flexible-pac-bayes-meta-learning

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More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms

https://github.com/hzakerinia/mtl

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From Low Intrinsic Dimensionality to Non-Vacuous Generalization Bounds in Deep Multi-Task Learning

https://github.com/insou/pop_minima

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On generalization bounds for deep networks based on loss surface implicit regularization

https://github.com/irom-lab/PAC-BUS

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Generalization Bounds for Meta-Learning via PAC-Bayes and Uniform Stability

https://github.com/irom-lab/PAC-Imitation

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Generalization Guarantees for Imitation Learning

https://github.com/jalb-epsilon/fine-tuning-nos

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Out-of-distributional risk bounds for neural operators with applications to the Helmholtz equation

https://github.com/jnegrea/neurips2019-5904-code

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Information-Theoretic Generalization Bounds for SGLD via Data-Dependent Estimates

https://github.com/jonasrothfuss/meta_learning_pacoh

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PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees

https://github.com/jsleb333/hypergeometric_tail_inversion

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Improving Generalization Bounds for VC Classes Using the Hypergeometric Tail Inversion

https://github.com/jwu4sml/grade

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Non-IID Transfer Learning on Graphs

https://github.com/kampmichael/RelativeFlatnessAndGeneralization

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Relative Flatness and Generalization

https://github.com/kazizzad/LabelShiftEstimator

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Importance Weight Estimation and Generalization in Domain Adaptation under Label Shift

https://github.com/khanrc/swad

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SWAD: Domain Generalization by Seeking Flat Minima

https://github.com/kid-7391/soprc

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Exploring the Algorithm-Dependent Generalization of AUPRC Optimization with List Stability

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