Summary of Aemlo: Autoencoder-guided Multi-label Oversampling, by Ao Zhou et al.
AEMLO: AutoEncoder-Guided Multi-Label Oversamplingby Ao Zhou, Bin Liu, Jin Wang, Kaiwei Sun, Kelin LiuFirst submitted…
Summary of Pcgrl+: Scaling, Control and Generalization in Reinforcement Learning Level Generators, by Sam Earle et al.
PCGRL+: Scaling, Control and Generalization in Reinforcement Learning Level Generatorsby Sam Earle, Zehua Jiang, Julian…
Summary of Criticality Leveraged Adversarial Training (clat) For Boosted Performance Via Parameter Efficiency, by Bhavna Gopal et al.
Criticality Leveraged Adversarial Training (CLAT) for Boosted Performance via Parameter Efficiencyby Bhavna Gopal, Huanrui Yang,…
Summary of Slca++: Unleash the Power Of Sequential Fine-tuning For Continual Learning with Pre-training, by Gengwei Zhang et al.
SLCA++: Unleash the Power of Sequential Fine-tuning for Continual Learning with Pre-trainingby Gengwei Zhang, Liyuan…
Summary of Adaptation Of Uncertainty-penalized Bayesian Information Criterion For Parametric Partial Differential Equation Discovery, by Pongpisit Thanasutives et al.
Adaptation of uncertainty-penalized Bayesian information criterion for parametric partial differential equation discoveryby Pongpisit Thanasutives, Ken-ichi…
Summary of Con-fold — Explainable Machine Learning with Confidence, by Lachlan Mcginness and Peter Baumgartner
CON-FOLD – Explainable Machine Learning with Confidenceby Lachlan McGinness, Peter BaumgartnerFirst submitted to arxiv on:…
Summary of Generalizing Few Data to Unseen Domains Flexibly Based on Label Smoothing Integrated with Distributionally Robust Optimization, by Yangdi Wang et al.
Generalizing Few Data to Unseen Domains Flexibly Based on Label Smoothing Integrated with Distributionally Robust…
Summary of Improving Fast Adversarial Training Paradigm: An Example Taxonomy Perspective, by Jie Gui et al.
Improving Fast Adversarial Training Paradigm: An Example Taxonomy Perspectiveby Jie Gui, Chengze Jiang, Minjing Dong,…
Summary of Parameter-efficient Electromagnetic Surrogate Solver For Broadband Field Prediction Using Discrete Wavelength Data, by Joonhyuk Seo et al.
Parameter-Efficient Electromagnetic Surrogate Solver for Broadband Field Prediction using Discrete Wavelength Databy Joonhyuk Seo, Chanik…
Summary of Bayesian Kolmogorov Arnold Networks (bayesian_kans): a Probabilistic Approach to Enhance Accuracy and Interpretability, by Masoud Muhammed Hassan
Bayesian Kolmogorov Arnold Networks (Bayesian_KANs): A Probabilistic Approach to Enhance Accuracy and Interpretabilityby Masoud Muhammed…