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Generalization

17 directly classified papers

Papers per year

Papers

Generalization of Graph Neural Networks Is Robust to Model Mismatch AAAI 2025
FreqDebias: Towards Generalizable Deepfake Detection via Consistency-Driven Frequency Debiasing CVPR 2025
Transcending Forgery Specificity with Latent Space Augmentation for Generalizable Deepfake Detection CVPR 2024
Understanding Scaling Laws with Statistical and Approximation Theory for Transformer Neural Networks on Intrinsically Low-dimensional Data NIPS 2024
An exactly solvable model for emergence and scaling laws in the multitask sparse parity problem NIPS 2024
AGAIN: Adversarial Training With Attribution Span Enlargement and Hybrid Feature Fusion CVPR 2023
Networks are Slacking Off: Understanding Generalization Problem in Image Deraining NIPS 2023
Reflash Dropout in Image Super-Resolution CVPR 2022
Exploiting Explainable Metrics for Augmented SGD CVPR 2022
Analyzing Lottery Ticket Hypothesis from PAC-Bayesian Theory Perspective NIPS 2022
Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions With Superior OOD Generalization CVPR 2022
Norm-Based Generalisation Bounds for Deep Multi-Class Convolutional Neural Networks AAAI 2021
In search of robust measures of generalization NIPS 2020
Computing the Testing Error Without a Testing Set CVPR 2020
Understanding Generalization in Neural Networks for Robustness against Adversarial Vulnerabilities AAAI 2020
High-Frequency Component Helps Explain the Generalization of Convolutional Neural Networks CVPR 2020
Understanding Data Augmentation in Neural Machine Translation: Two Perspectives towards Generalization EMNLP 2019