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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/sagiebenaim/gan_bound

공식 코드

Estimating the Success of Unsupervised Image to Image Translation

https://github.com/saisrivatsan/deep-opt-auctions

공식 코드

Optimal Auctions through Deep Learning: Advances in Differentiable Economics

https://github.com/sanaelotfi/sublora-bounds-for-llms

공식 코드

Non-Vacuous Generalization Bounds for Large Language Models

https://github.com/sangdon/PAC-confidence-set

공식 코드

PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction

https://github.com/shoelim/mpgd

공식 코드

Chaotic Regularization and Heavy-Tailed Limits for Deterministic Gradient Descent

https://github.com/simone-bombari/attention-sensitivity

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Towards Understanding the Word Sensitivity of Attention Layers: A Study via Random Features

https://github.com/sorooshafiee/Regularization-via-Transportation

공식 코드

Regularization via Mass Transportation

https://github.com/spratm-asleaf/robustness-specificity

공식 코드

Learning Against Distributional Uncertainty: On the Trade-off Between Robustness and Specificity

https://github.com/stellatogrp/l2ws_fixed_point

공식 코드

Learning to Warm-Start Fixed-Point Optimization Algorithms

https://github.com/suehiro93/mil_reduction

공식 코드

Simplified and Unified Analysis of Various Learning Problems by Reduction to Multiple-Instance Learning

https://github.com/sumukhaithal6/pgdl

공식 코드

Robustness to Augmentations as a Generalization metric

https://github.com/sunxin000/uncertainty4recsys

공식 코드

Uncertainty Calibration for Counterfactual Propensity Estimation in Recommendation

https://github.com/sylydya/Consistent-Sparse-Deep-Learning-Theory-and-Computation

공식 코드

Consistent Sparse Deep Learning: Theory and Computation

https://github.com/tencentailabhealthcare/umix

공식 코드

UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup

https://github.com/thejat/supervised_learning_with_side_knowledge

공식 코드

Generalization Bounds for Learning with Linear, Polygonal, Quadratic and Conic Side Knowledge

https://github.com/theophilec/PAC-Bayes-ILE-Structured-Prediction

공식 코드

A PAC-Bayesian Perspective on Structured Prediction with Implicit Loss Embeddings

https://github.com/thuml/MDD

공식 코드

Bridging Theory and Algorithm for Domain Adaptation

https://github.com/tobsutter/pmdi_dro

공식 코드

Robust Generalization despite Distribution Shift via Minimum Discriminating Information

https://github.com/traugerjacob/transformer-gen-bounds

공식 코드

Sequence Length Independent Norm-Based Generalization Bounds for Transformers

https://github.com/umarteau/Newton-Method-for-GSC-losses-

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Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses

https://github.com/umutsimsekli/Hausdorff-Dimension-and-Generalization

공식 코드

Hausdorff Dimension, Heavy Tails, and Generalization in Neural Networks

https://github.com/vikasverma1077/GraphMix

공식 코드

GraphMix: Improved Training of GNNs for Semi-Supervised Learning

https://github.com/virtuosoresearch/generalization-in-graph-neural-networks

공식 코드

Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion

https://github.com/virtuosoresearch/robust-fine-tuning

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Robust Fine-Tuning of Deep Neural Networks with Hessian-based Generalization Guarantees

https://github.com/vzantedeschi/StocMV

공식 코드

Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound

https://github.com/wendazhou/nnet-compression-generalization

공식 코드

Non-Vacuous Generalization Bounds at the ImageNet Scale: A PAC-Bayesian Compression Approach

https://github.com/xialeiliu/Awesome-Incremental-Learning

공식 코드

The Ideal Continual Learner: An Agent That Never Forgets

https://github.com/xiwei-cheng/stability_freeat

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Stability and Generalization in Free Adversarial Training

https://github.com/xjtushujun/slem-theory

공식 코드

Learning an Explicit Hyperparameter Prediction Function Conditioned on Tasks

https://github.com/xu-ji/information-bottleneck

공식 코드

How Does Information Bottleneck Help Deep Learning?

https://github.com/xxgege/nico-plus

공식 코드

NICO++: Towards Better Benchmarking for Domain Generalization

https://github.com/yashpatel5400/schrodinger_op

공식 코드

Operator Learning for Schrödinger Equation: Unitarity, Error Bounds, and Time Generalization

https://github.com/yifanwang123/Generalization-Performance-of-Hypergraph-Neural-Networks

공식 코드

Generalization Performance of Hypergraph Neural Networks

https://github.com/yingcong-li/transformers-as-algorithms

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Transformers as Algorithms: Generalization and Stability in In-context Learning

https://github.com/yu-group/imodels-experiments

공식 코드

Fast Interpretable Greedy-Tree Sums

https://github.com/zhenhuan-yang/minimax-stability

공식 코드

Stability and Generalization of Stochastic Gradient Methods for Minimax Problems

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