Data Ablation
4 papers with code • 0 benchmarks • 0 datasets
Data Ablation is the study of change in data, and its effects in the performance of Neural Networks.
Benchmarks
These leaderboards are used to track progress in Data Ablation
Most implemented papers
AI Playground: Unreal Engine-based Data Ablation Tool for Deep Learning
With AIP, it is trivial to capture the same image under different conditions (e. g., fidelity, lighting, etc.)
Understanding Robust Overfitting of Adversarial Training and Beyond
chaojianyu/understanding-robust-overfitting
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Here, we explore the causes of robust overfitting by comparing the data distribution of \emph{non-overfit} (weak adversary) and \emph{overfitted} (strong adversary) adversarial training, and observe that the distribution of the adversarial data generated by weak adversary mainly contain small-loss data.
Multi-horizon short-term load forecasting using hybrid of LSTM and modified split convolution
The concatenating order of LSTM and SC in the proposed hybrid network provides an excellent capability of extraction of sequence-dependent features and other hierarchical spatial features.
Alzheimer's disease detection in PSG signals
This study delves into the potential of utilizing sleep-related electroencephalography (EEG) signals acquired through polysomnography (PSG) for the early detection of AD.
