Deep Learning
Learning to Detect Objects with a 1 Megapixel Event Camera
Second, we introduce a novel recurrent architecture for event-based detection and a temporal consistency loss for better-behaved training.
Fitting summary statistics of neural data with a differentiable spiking network simulator
Fitting network models to neural activity is an important tool in neuroscience.
Optimal Variance Control of the Score Function Gradient Estimator for Importance Weighted Bounds Valentin Liรฉvin 1 Andrea Dittadi 1 Anders Christensen
We will compare the different estimators on the basis of their Signal-to-noise ratio.
BulletTrain: Accelerating Robust Neural Network Training via Boundary Example Mining Weizhe Hua
Neural network robustness has become a central topic in machine learning in recent years. Most training algorithms that improve the model's robustness to