Deep Learning
DoResidualNeuralNetworksdiscretizeNeural OrdinaryDifferentialEquations?
Neural ODEs also provide atheoretical framework to study deep learning models from the continuous viewpoint, using the arsenal of ODE theory [40, 25, 41]. Importantly, they can also be seen as the continuous analog of ResNets.
Dancing to Music
Hsin-Ying Lee, Xiaodong Yang, Ming-Yu Liu, Ting-Chun Wang, Yu-Ding Lu, Ming-Hsuan Yang, Jan Kautz
Neural Information Processing Systems http://nips.cc/
Finding Order in Chaos: A Novel Data Augmentation Method for Time Series in Contrastive Learning
The success of contrastive learning is well known to be dependent on data augmentation.
Hybrid Macro/Micro Level Backpropagation for Training Deep Spiking Neural Networks
Yingyezhe Jin, Wenrui Zhang, Peng Li
Neural Information Processing Systems http://nips.cc/
Predictive Uncertainty Estimation via Prior Networks
Neural Information Processing Systems http://nips.cc/
TrainingwithMoreConfidence: MitigatingInjected andNaturalBackdoorsDuringTraining
Researchers find that DNNs trained on benign data and settings can also learn backdoor behaviors, which is known as the natural backdoor.
