Summary of Searching For Internal Symbols Underlying Deep Learning, by Jung H. Lee et al.
Searching for internal symbols underlying deep learningby Jung H. Lee, Sujith VijayanFirst submitted to arxiv…
Searching for internal symbols underlying deep learningby Jung H. Lee, Sujith VijayanFirst submitted to arxiv…
Deep Modeling of Non-Gaussian Aleatoric Uncertaintyby Aastha Acharya, Caleb Lee, Marissa D'Alonzo, Jared Shamwell, Nisar…
Uncertainty Quantification for Deep Learningby Peter Jan van Leeuwen, J. Christine Chiu, C. Kevin YangFirst…
Class-Based Time Series Data Augmentation to Mitigate Extreme Class Imbalance for Solar Flare Predictionby Junzhi…
Knockout: A simple way to handle missing inputsby Minh Nguyen, Batuhan K. Karaman, Heejong Kim,…
Optimizing cnn-Bigru performance: Mish activation and comparative analysis with Reluby Asmaa Benchama, Khalid ZebbaraFirst submitted…
Back to the Basics on Predicting Transfer Performanceby Levy Chaves, Eduardo Valle, Alceu Bissoto, Sandra…
Occam Gradient Descentby B.N. KausikFirst submitted to arxiv on: 30 May 2024CategoriesMain: Machine Learning (cs.LG)Secondary:…
Unified Explanations in Machine Learning Models: A Perturbation Approachby Jacob Dineen, Don Kridel, Daniel Dolk,…
Feature Fusion for Improved Classification: Combining Dempster-Shafer Theory and Multiple CNN Architecturesby Ayyub Alzahem, Wadii…