{"total":21,"rows":[{"id":"2106.14448","title":"R-Drop: Regularized Dropout for Neural Networks","created":"2021-06-28","cited_by_count":202,"area":null},{"id":"2202.08345","title":"Learning Smooth Neural Functions via Lipschitz Regularization","created":"2022-02-16","cited_by_count":86,"area":null},{"id":"2402.02769","title":"Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate","created":"2024-02-05","cited_by_count":47,"area":null},{"id":"2106.10185","title":"NoiseGrad: Enhancing Explanations by Introducing Stochasticity to Model Weights","created":"2021-06-18","cited_by_count":28,"area":null},{"id":"2102.07379","title":"On the Inherent Regularization Effects of Noise Injection During Training","created":"2021-02-15","cited_by_count":18,"area":null},{"id":"2102.07006","title":"Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections","created":"2021-02-13","cited_by_count":12,"area":null},{"id":"2408.15300","title":"GIFT-SW: Gaussian noise Injected Fine-Tuning of Salient Weights for LLMs","created":"2024-08-27","cited_by_count":8,"area":null},{"id":"2310.18626","title":"Benchmark Generation Framework with Customizable Distortions for Image Classifier Robustness","created":"2023-10-28","cited_by_count":7,"area":null},{"id":"2201.06759","title":"Knowledge Sharing via Domain Adaptation in Customs Fraud Detection","created":"2022-01-18","cited_by_count":5,"area":null},{"id":"2302.12304","title":"Uncertainty Injection: A Deep Learning Method for Robust Optimization","created":"2023-02-23","cited_by_count":5,"area":null},{"id":"2306.17630","title":"Navigating Noise: A Study of How Noise Influences Generalisation and Calibration of Neural Networks","created":"2023-06-30","cited_by_count":4,"area":null},{"id":"2411.03186","title":"Insights into Lunar Mineralogy: An Unsupervised Approach for Clustering of the Moon Mineral Mapper (M3) spectral data","created":"2024-11-05","cited_by_count":2,"area":null},{"id":"2202.09248","title":"Stochastic Perturbations of Tabular Features for Non-Deterministic Inference with Automunge","created":"2022-02-18","cited_by_count":1,"area":null},{"id":"2110.05003","title":"Disturbing Target Values for Neural Network Regularization","created":"2021-10-11","cited_by_count":0,"area":null},{"id":"2205.10122","title":"Stochastic resonance neurons in artificial neural networks","created":"2022-05-06","cited_by_count":0,"area":null},{"id":"2303.09630","title":"Hyper-Reduced Autoencoders for Efficient and Accurate Nonlinear Model Reductions","created":"2023-03-16","cited_by_count":0,"area":null},{"id":"2402.16361","title":"Layer-wise Regularized Dropout for Neural Language Models","created":"2024-02-26","cited_by_count":0,"area":null},{"id":"2407.13685","title":"Beyond Trend Following: Deep Learning for Market Trend Prediction","created":"2024-06-10","cited_by_count":0,"area":null},{"id":"2410.06348","title":"Harnessing the Power of Noise: A Survey of Techniques and Applications","created":"2024-10-08","cited_by_count":0,"area":null},{"id":"2505.24525","title":"Limited-Resource Adapters Are Regularizers, Not Linguists","created":"2025-05-30","cited_by_count":0,"area":null},{"id":"2512.13707","title":"Modular connectivity in neural networks emerges from Poisson noise-motivated regularisation, and promotes robustness and compositional generalisation","created":"2025-12-05","cited_by_count":0,"area":null}],"next_cursor":null}