Timothy P. Lillicrap

According to our database1, Timothy P. Lillicrap authored at least 51 papers between 2008 and 2018.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

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Homepages:

On csauthors.net:

Bibliography

2018
Optimizing Agent Behavior over Long Time Scales by Transporting Value.
CoRR, 2018

Episodic Curiosity through Reachability.
CoRR, 2018

Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors.
CoRR, 2018

Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures.
CoRR, 2018

Measuring abstract reasoning in neural networks.
CoRR, 2018

Relational Deep Reinforcement Learning.
CoRR, 2018

Relational recurrent neural networks.
CoRR, 2018

Distributed Distributional Deterministic Policy Gradients.
CoRR, 2018

The Kanerva Machine: A Generative Distributed Memory.
CoRR, 2018

Recall Traces: Backtracking Models for Efficient Reinforcement Learning.
CoRR, 2018

Unsupervised Predictive Memory in a Goal-Directed Agent.
CoRR, 2018

Fast Parametric Learning with Activation Memorization.
CoRR, 2018

DeepMind Control Suite.
CoRR, 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

2017
Deep Learning with Dynamic Spiking Neurons and Fixed Feedback Weights.
Neural Computation, 2017

Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm.
CoRR, 2017

Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017.
CoRR, 2017

StarCraft II: A New Challenge for Reinforcement Learning.
CoRR, 2017

A simple neural network module for relational reasoning.
CoRR, 2017

Discovering objects and their relations from entangled scene representations.
CoRR, 2017

Data-efficient Deep Reinforcement Learning for Dexterous Manipulation.
CoRR, 2017

Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning.
CoRR, 2017

Generative Temporal Models with Memory.
CoRR, 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

2016
Mastering the game of Go with deep neural networks and tree search.
Nature, 2016

Matching Networks for One Shot Learning.
CoRR, 2016

One-shot Learning with Memory-Augmented Neural Networks.
CoRR, 2016

Scaling Memory-Augmented Neural Networks with Sparse Reads and Writes.
CoRR, 2016

Asynchronous Methods for Deep Reinforcement Learning.
CoRR, 2016

Learning and Transfer of Modulated Locomotor Controllers.
CoRR, 2016

Continuous Deep Q-Learning with Model-based Acceleration.
CoRR, 2016

Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic.
CoRR, 2016

Deep Reinforcement Learning for Robotic Manipulation.
CoRR, 2016

Learning to Learn for Global Optimization of Black Box Functions.
CoRR, 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
Towards Principled Unsupervised Learning.
CoRR, 2015

Continuous control with deep reinforcement learning.
CoRR, 2015

Learning Continuous Control Policies by Stochastic Value Gradients.
CoRR, 2015

Memory-based control with recurrent neural networks.
CoRR, 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

2014
Random feedback weights support learning in deep neural networks.
CoRR, 2014

2012
Relevance Realization and the Emerging Framework in Cognitive Science.
J. Log. Comput., 2012

2008
Sensitivity Derivatives for Flexible Sensorimotor Learning.
Neural Computation, 2008


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