NewEvery arXiv paper, its researchers & institutions — mapped.
papers

Publications (62)

cs.LG2017

StarCraft II: A New Challenge for Reinforcement Learning

Oriol Vinyals, Timo Ewalds, Sergey Bartunov +22

cs.AI2018

DeepMind Control Suite

Yuval Tassa, Yotam Doron, Alistair Muldal +9

cs.CL2017

A simple neural network module for relational reasoning

Adam Santoro, David Raposo, David G. T. Barrett +4

cs.RO2020

dm_control: Software and Tasks for Continuous Control

Yuval Tassa, Saran Tunyasuvunakool, Alistair Muldal +8

cs.AI2017

Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

David Silver, Thomas Hubert, Julian Schrittwieser +10

cs.LG2021

Imitating Interactive Intelligence

Josh Abramson, Arun Ahuja, Iain Barr +26

cs.LG2020

Deep Learning without Weight Transport

Mohamed Akrout, Collin Wilson, Peter C. Humphreys +2

cs.LG2017

Data-efficient Deep Reinforcement Learning for Dexterous Manipulation

Ivaylo Popov, Nicolas Heess, Timothy Lillicrap +7

cs.AI2016

Deep Reinforcement Learning in Large Discrete Action Spaces

Gabriel Dulac-Arnold, Richard Evans, Hado van Hasselt +7

cs.AI2025

Training Agents Inside of Scalable World Models

Danijar Hafner, Wilson Yan, Timothy Lillicrap

stat.ML2018

The Kanerva Machine: A Generative Distributed Memory

Yan Wu, Greg Wayne, Alex Graves +1

cs.LG2017

Matching Networks for One Shot Learning

Oriol Vinyals, Charles Blundell, Timothy Lillicrap +2

cs.LG2022

A data-driven approach for learning to control computers

Peter C Humphreys, David Raposo, Toby Pohlen +8

cs.LG2017

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

Shixiang Gu, Timothy Lillicrap, Zoubin Ghahramani +3

cs.CL2024

Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Gemini Team, Petko Georgiev, Ving Ian Lei +1132

cs.LG2023

Android in the Wild: A Large-Scale Dataset for Android Device Control

Christopher Rawles, Alice Li, Daniel Rodriguez +2

cs.LG2022

Improving Multimodal Interactive Agents with Reinforcement Learning from Human Feedback

Josh Abramson, Arun Ahuja, Federico Carnevale +16

cs.LG2018

Relational recurrent neural networks

Adam Santoro, Ryan Faulkner, David Raposo +7

cs.AI2024

Mastering Diverse Domains through World Models

Danijar Hafner, Jurgis Pasukonis, Jimmy Ba +1

cs.LG2020

Beyond Tabula-Rasa: a Modular Reinforcement Learning Approach for Physically Embedded 3D Sokoban

Peter Karkus, Mehdi Mirza, Arthur Guez +5

q-bio.NC2019

Is coding a relevant metaphor for building AI? A commentary on "Is coding a relevant metaphor for the brain?", by Romain Brette

Adam Santoro, Felix Hill, David Barrett +3

stat.ML2019

Noise Contrastive Priors for Functional Uncertainty

Danijar Hafner, Dustin Tran, Timothy Lillicrap +2

cs.LG2019

An investigation of model-free planning

Arthur Guez, Mehdi Mirza, Karol Gregor +10

cs.LG2017

Discovering objects and their relations from entangled scene representations

David Raposo, Adam Santoro, David Barrett +3

cs.LG2022

Evaluating Multimodal Interactive Agents

Josh Abramson, Arun Ahuja, Federico Carnevale +12

cs.LG2022

Mastering Atari with Discrete World Models

Danijar Hafner, Timothy Lillicrap, Mohammad Norouzi +1

cs.LG2018

Measuring abstract reasoning in neural networks

David G. T. Barrett, Felix Hill, Adam Santoro +2

cs.AI2018

Optimizing Agent Behavior over Long Time Scales by Transporting Value

Chia-Chun Hung, Timothy Lillicrap, Josh Abramson +5

cs.LG2020

Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model

Julian Schrittwieser, Ioannis Antonoglou, Thomas Hubert +9

cs.LG2024

Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

David Raposo, Sam Ritter, Blake Richards +3

cs.LG2017

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

Shixiang Gu, Timothy Lillicrap, Zoubin Ghahramani +2

cs.AI2019

Learning to Make Analogies by Contrasting Abstract Relational Structure

Felix Hill, Adam Santoro, David G. T. Barrett +2

cs.CL2025

Gemini: A Family of Highly Capable Multimodal Models

Gemini Team, Rohan Anil, Sebastian Borgeaud +1340

cs.LG2022

Equilibrium Aggregation: Encoding Sets via Optimization

Sergey Bartunov, Fabian B. Fuchs, Timothy Lillicrap

cs.LG2016

Continuous Deep Q-Learning with Model-based Acceleration

Shixiang Gu, Timothy Lillicrap, Ilya Sutskever +1

cs.LG2018

Distributed Distributional Deterministic Policy Gradients

Gabriel Barth-Maron, Matthew W. Hoffman, David Budden +6

cs.LG2022

Intra-agent speech permits zero-shot task acquisition

Chen Yan, Federico Carnevale, Petko Georgiev +7

cs.LG2019

Learning Latent Dynamics for Planning from Pixels

Danijar Hafner, Timothy Lillicrap, Ian Fischer +4

cs.AI2023

Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution

Anthony Zador, Sean Escola, Blake Richards +24

cs.AI2022

Symbolic Behaviour in Artificial Intelligence

Adam Santoro, Andrew Lampinen, Kory Mathewson +2

cs.LG2019

Recall Traces: Backtracking Models for Efficient Reinforcement Learning

Anirudh Goyal, Philemon Brakel, William Fedus +5

cs.LG2018

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

Sergey Bartunov, Adam Santoro, Blake A. Richards +3

cs.LG2022

Retrieval-Augmented Reinforcement Learning

Anirudh Goyal, Abram L. Friesen, Andrea Banino +13

cs.LG2018

Learning Attractor Dynamics for Generative Memory

Yan Wu, Greg Wayne, Karol Gregor +1

cs.LG2022

Creating Multimodal Interactive Agents with Imitation and Self-Supervised Learning

DeepMind Interactive Agents Team, Josh Abramson, Arun Ahuja +22

cs.LG2018

Relational Deep Reinforcement Learning

Vinicius Zambaldi, David Raposo, Adam Santoro +13

cs.LG2019

Episodic Curiosity through Reachability

Nikolay Savinov, Anton Raichuk, Raphaël Marinier +4

cs.LG2018

Unsupervised Predictive Memory in a Goal-Directed Agent

Greg Wayne, Chia-Chun Hung, David Amos +21

cs.LG2016

One-shot Learning with Memory-Augmented Neural Networks

Adam Santoro, Sergey Bartunov, Matthew Botvinick +2

cs.LG2015

Learning Continuous Control Policies by Stochastic Value Gradients

Nicolas Heess, Greg Wayne, David Silver +3

cs.RO2016

Deep Reinforcement Learning for Robotic Manipulation with Asynchronous Off-Policy Updates

Shixiang Gu, Ethan Holly, Timothy Lillicrap +1

cs.CL2025

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Gheorghe Comanici, Eric Bieber, Mike Schaekermann +3431

cs.RO2016

Learning and Transfer of Modulated Locomotor Controllers

Nicolas Heess, Greg Wayne, Yuval Tassa +3

cs.AI2025

AndroidWorld: A Dynamic Benchmarking Environment for Autonomous Agents

Christopher Rawles, Sarah Clinckemaillie, Yifan Chang +12

cs.LG2020

Dream to Control: Learning Behaviors by Latent Imagination

Danijar Hafner, Timothy Lillicrap, Jimmy Ba +1

cs.LG2019

Deep Compressed Sensing

Yan Wu, Mihaela Rosca, Timothy Lillicrap

cs.AI2020

Physically Embedded Planning Problems: New Challenges for Reinforcement Learning

Mehdi Mirza, Andrew Jaegle, Jonathan J. Hunt +9

cs.LG2017

Generative Temporal Models with Memory

Mevlana Gemici, Chia-Chun Hung, Adam Santoro +5

cs.AI2022

Evaluating Long-Term Memory in 3D Mazes

Jurgis Pasukonis, Timothy Lillicrap, Danijar Hafner

cs.LG2022

Large-Scale Retrieval for Reinforcement Learning

Peter C. Humphreys, Arthur Guez, Olivier Tieleman +3

cs.LG2020

LOGAN: Latent Optimisation for Generative Adversarial Networks

Yan Wu, Jeff Donahue, David Balduzzi +2

cs.AI2024

Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving

Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke +7