# Timothy P. Lillicrap

According to our database

Collaborative distances:

^{1}, Timothy P. Lillicrap authored at least 24 papers between 2008 and 2018.Collaborative distances:

## Timeline

#### Legend:

Book In proceedings Article PhD thesis Other## Links

#### Homepages:

#### On csauthors.net:

## Bibliography

2018

Learning Attractor Dynamics for Generative Memory.

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Relational recurrent neural networks.

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures.

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Measuring abstract reasoning in neural networks.

Proceedings of the 35th International Conference on Machine Learning, 2018

Fast Parametric Learning with Activation Memorization.

Proceedings of the 35th International Conference on Machine Learning, 2018

The Kanerva Machine: A Generative Distributed Memory.

Proceedings of the 6th International Conference on Learning Representations, 2018

Distributed Distributional Deterministic Policy Gradients.

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Deep Learning with Dynamic Spiking Neurons and Fixed Feedback Weights.

Neural Computation, 2017

A simple neural network module for relational reasoning.

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning.

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates.

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Learning to Learn without Gradient Descent by Gradient Descent.

Proceedings of the 34th International Conference on Machine Learning, 2017

Discovering objects and their relations from entangled scene representations.

Proceedings of the 5th International Conference on Learning Representations, 2017

Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic.

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Mastering the game of Go with deep neural networks and tree search.

Nature, 2016

Continuous control with deep reinforcement learning.

Proceedings of the 4th International Conference on Learning Representations, 2016

Matching Networks for One Shot Learning.

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Scaling Memory-Augmented Neural Networks with Sparse Reads and Writes.

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Meta-Learning with Memory-Augmented Neural Networks.

Proceedings of the 33nd International Conference on Machine Learning, 2016

Asynchronous Methods for Deep Reinforcement Learning.

Proceedings of the 33nd International Conference on Machine Learning, 2016

Continuous Deep Q-Learning with Model-based Acceleration.

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Learning Continuous Control Policies by Stochastic Value Gradients.

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2012

Relevance Realization and the Emerging Framework in Cognitive Science.

J. Log. Comput., 2012

2008

Sensitivity Derivatives for Flexible Sensorimotor Learning.

Neural Computation, 2008