Abstract  Description  Claims  Drawing  Search report  Cited references 

US20200074305A   [0005]  [0007] 

Dark experience for general continual learning: a strong, simple baseline   [0030] 
euroscience-inspired artificial intelligence   [0030] 
The stability-plasticity dilemma: Investigating the continuum from catastrophic forgetting to age-limited learning effects   [0030] 
Connectionist models of recognition memory: constraints imposed by learning and forgetting functions   [0030] 
Gradient episodic memory for continual learning   [0030] 
Efficient lifelong learning witha-gem   [0030] 
Lampert. icarl: Incremental classifier and representation learning   [0030] 
Learning with pseudo-ensembles   [0030] 
S4l: Self-supervised semi-supervised learning   [0030] 
Regularization with stochastic transformations and perturbations for deep semi-supervised learning   [0030] 
Virtual adversarial training: a regularization method for supervised and semi-supervised learning   [0030] 
Measuring and regularizing networks in function space   [0030] 
Learning fast, learning slow: A general continual learning method based on complementary learning system   [0030] 
An empirical investigation of catastrophic forgetting in gradient-based neural networks   [0030] 
Continual lifelong learning with neural networks: A review   [0030] 
Continual learning through synaptic intelligence   [0030] 
Progress & compress: A scalable framework for continual learning   [0030] 
Progressive neural networks   [0030] 
Towards robust evaluations of continual learning   [0030] 
Learning multiple layers of features from tiny images   [0030] 
Gradient episodic memory for continual learning   [0030] 
Gradient-based learning applied to document recognition   [0030] 
Deep residual learning for image recognition.   [0030]