Timothy Lillicrap
41 papers · 2015–2024 · 4 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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πΊοΈ Taxonomy Completionist (67) π Academic Marathon Β· Sprint π Conference Polyglot Β· Bronze π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Deep Specialist
(14)
π€
Dynamic Duo
(11)
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Triple Crown
π
Keyword Trendsetter Combo
(4)
π
Keyword Champion
π§
Keyword Pioneer
π
Trend Setter
π₯
Unstoppable Β· Silver
β‘
Prolific Year Β· Prolific
ποΈ
Keyword Collector
(197)
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Renaissance Researcher
(6)
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Century Club Β· Bronze
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Conference Pioneer
Venues
Top co-authors
Research topics
Machine Learning
(29)
Deep Learning
(24)
Artificial Intelligence
(18)
Reinforcement Learning
(16)
Methods
(16)
Learning Types Β· Machine Learning
(15)
Learning Types Β· Deep Learning
(14)
Core AI
(11)
Core Methods
(11)
Optimization & Theory
(11)
Architectures
(9)
Learning Paradigms
(8)
Applications
(6)
Models
(6)
Application Areas
(4)
Keywords
neural network
(8)
continuous control
(7)
deep reinforcement learning
(5)
reinforcement learning
(5)
one-shot learning
(4)
model-based reinforcement learning
(4)
few-shot learning
(3)
variational inference
(3)
relational reasoning
(3)
off-policy learning
(3)
generative adversarial network
(2)
biologically plausible learning
(2)
convolutional network
(2)
generative model
(2)
retrieval-augmented generation
(2)
sample efficiency
(2)
value function
(2)
language modeling
(2)
offline reinforcement learning
(2)
policy gradient
(2)
Papers
Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving
NeurIPS 2024
AndroidInTheWild: A Large-Scale Dataset For Android Device Control
NeurIPS 2023
A data-driven approach for learning to control computers
ICML 2022
Intra-agent speech permits zero-shot task acquisition
NeurIPS 2022
Large-Scale Retrieval for Reinforcement Learning
NeurIPS 2022
On the Stability and Scalability of Node Perturbation Learning
NeurIPS 2022
Retrieval-Augmented Reinforcement Learning
ICML 2022
The functional specialization of visual cortex emerges from training parallel pathways with self-supervised predictive learning
NeurIPS 2021
Towards Biologically Plausible Convolutional Networks
NeurIPS 2021
A meta-learning approach to (re)discover plasticity rules that carve a desired function into a neural network
NeurIPS 2020
Automated curriculum generation through setter-solver interactions
ICLR 2020
Dream to Control: Learning Behaviors by Latent Imagination
ICLR 2020
Meta-Learning Deep Energy-Based Memory Models
ICLR 2020
Training Generative Adversarial Networks by Solving Ordinary Differential Equations
NeurIPS 2020
An Investigation of Model-Free Planning
ICML 2019
Composing Entropic Policies using Divergence Correction
ICML 2019
Deep Compressed Sensing
ICML 2019
Deep Learning without Weight Transport
NeurIPS 2019
Deep reinforcement learning with relational inductive biases
ICLR 2019
Episodic Curiosity through Reachability
ICLR 2019
Experience Replay for Continual Learning
NeurIPS 2019
Learning Latent Dynamics for Planning from Pixels
ICML 2019
Learning to Make Analogies by Contrasting Abstract Relational Structure
ICLR 2019
Meta-Learning Neural Bloom Filters
ICML 2019
Noise Contrastive Priors for Functional Uncertainty
UAI 2019
Recall Traces: Backtracking Models for Efficient Reinforcement Learning
ICLR 2019
Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures
NeurIPS 2018
Distributed Distributional Deterministic Policy Gradients
ICLR 2018
Fast Parametric Learning with Activation Memorization
ICML 2018
Learning Attractor Dynamics for Generative Memory
NeurIPS 2018
Measuring abstract reasoning in neural networks
ICML 2018
Relational recurrent neural networks
NeurIPS 2018
The Kanerva Machine: A Generative Distributed Memory
ICLR 2018
A simple neural network module for relational reasoning
NeurIPS 2017
Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning
NeurIPS 2017
Asynchronous Methods for Deep Reinforcement Learning
ICML 2016
Continuous Deep Q-Learning with Model-based Acceleration
ICML 2016
Matching Networks for One Shot Learning
NeurIPS 2016
Meta-Learning with Memory-Augmented Neural Networks
ICML 2016
Scaling Memory-Augmented Neural Networks with Sparse Reads and Writes
NeurIPS 2016
Learning Continuous Control Policies by Stochastic Value Gradients
NeurIPS 2015