Towards Deep Developmental Learning
Explore this paper's citation graph
- Type
- article
- Published
- 2016-06-01
- Cited by
- 47
- References
- 171
- Access
- Open access
- OpenAlex
- https://openalex.org/W2344656918
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:14309457
Keywords
Artificial intelligence, Deep learning, Computer science, Hierarchy, Construct (python library)
References
- Self-organized formation of topologically correct feature maps
- Two Distributed-State Models For Generating High-Dimensional Time Series
- Probabilistic Graphical Models: Principles and Techniques - Adaptive Computation and Machine Learning
- Deep Boltzmann Machines
- Generating Text with Recurrent Neural Networks
- Deep learning via Hessian-free optimization
- Many regression algorithms, one unified model: A review
- Theories of developmental psychology
- Long Short-Term Memory Based Recurrent Neural Network Architectures for Large Vocabulary Speech Recognition
- Gradient Flow in Recurrent Nets: the Difficulty of Learning Long-Term Dependencies
- Sequence Labelling in Structured Domains with Hierarchical Recurrent Neural Networks
- Understanding the difficulty of training deep feedforward neural networks
- Supersizing the Mind
- Supersizing the Mind: Embodiment, Action and Cognitive Extension.
- Gated Autoencoders with Tied Input Weights
- The construction of reality in the child
- Information processing in dynamical systems: foundations of harmony theory
- Curious model-building control systems
- An exact mapping between the Variational Renormalization Group and Deep Learning
- Improving neural networks by preventing co-adaptation of feature detectors
Cited by
- Place Classification With a Graph Regularized Deep Neural Network
- Gated networks: an inventory
- Unsupervised Learning from Continuous Video in a Scalable Predictive Recurrent Network
- Value systems for developmental cognitive robotics: A survey
- A novel training algorithm for convolutional neural network
- Towards Lifelong Self-Supervision: A Deep Learning Direction for Robotics
- Training Agents With Interactive Reinforcement Learning and Contextual Affordances
- A deep learning approach for seamless integration of cognitive skills for humanoid robots
- Towards a common implementation of reinforcement learning for multiple robotic tasks
- Learning representation hierarchies by sharing visual features: a computational investigation of Persian character recognition with unsupervised deep learning
- Growing a Brain: Fine-Tuning by Increasing Model Capacity
- Deep Active Learning Through Cognitive Information Parcels
- An embodied model for handwritten digits recognition in a cognitive robot
- An Extended Reinforcement Learning Framework to Model Cognitive Development With Enactive Pattern Representation
- Experiential robot learning with deep neural networks
- Potentials and Limitations of Deep Neural Networks for Cognitive Robots
- Learning to Learn for Small Sample Visual Recognition
- Long-Short Term Memory Networks for Modelling Embodied Mathematical Cognition in Robots
- Small Sample Learning in Big Data Era
- Optimizing the Capacity of a Convolutional Neural Network for Image Segmentation and Pattern Recognition
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