643 citations · 2.1k across the 8 of their papers we have counts for
11 papers
Collective Intelligence for Deep Learning: A Survey of Recent Developments
David Ha, Yujin Tang
In the past decade, we have witnessed the rise of deep learning to dominate the field of artificial intelligence. Advances in artificial neural networks alongside corresponding adv…
The Sensory Neuron as a Transformer: Permutation-Invariant Neural Networks for Reinforcement Learning
Yujin Tang, David Ha
In complex systems, we often observe complex global behavior emerge from a collection of agents interacting with each other in their environment, with each individual agent acting…
Weight Agnostic Neural Networks
Adam Gaier, David Ha
Not all neural network architectures are created equal, some perform much better than others for certain tasks. But how important are the weight parameters of a neural network comp…
A Learned Representation for Scalable Vector Graphics
Raphael Gontijo Lopes, David Ha, Douglas Eck +1
Dramatic advances in generative models have resulted in near photographic quality for artificially rendered faces, animals and other objects in the natural world. In spite of such…
Learning Latent Dynamics for Planning from Pixels
Danijar Hafner, Timothy Lillicrap, Ian Fischer +4
Planning has been very successful for control tasks with known environment dynamics. To leverage planning in unknown environments, the agent needs to learn the dynamics from intera…
Reinforcement Learning for Improving Agent Design
David Ha
In many reinforcement learning tasks, the goal is to learn a policy to manipulate an agent, whose design is fixed, to maximize some notion of cumulative reward. The design of the a…