Jack W. Rae

发表

Top-KAST: Top-K Always Sparse Training

Razvan Pascanu, Simon Osindero, Siddhant M. Jayakumar, 2021, NeurIPS.

Neural Arithmetic Logic Units

Chris Dyer, Felix Hill, Phil Blunsom, 2018, NeurIPS.

Relational recurrent neural networks

Razvan Pascanu, Oriol Vinyals, Daan Wierstra, 2018, NeurIPS.

Fast Parametric Learning with Activation Memorization

Peter Dayan, Chris Dyer, Timothy P. Lillicrap, 2018, ICML.

Unsupervised Predictive Memory in a Goal-Directed Agent pdf

Joel Z. Leibo, Demis Hassabis, Koray Kavukcuoglu, 2018, ArXiv.

Stabilizing Transformers for Reinforcement Learning

Razvan Pascanu, H. Francis Song, Raia Hadsell, 2019, ICML.

Memory-based Parameter Adaptation pdf

Razvan Pascanu, Demis Hassabis, Oriol Vinyals, 2018, ICLR.

Multiplicative Interactions and Where to Find Them

Yee Whye Teh, Razvan Pascanu, Simon Osindero, 2020, ICLR.

Training language GANs from Scratch

Shakir Mohamed, Jack W. Rae, Mihaela Rosca, 2019, NeurIPS.

V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control pdf

H. Francis Song, Martin A. Riedmiller, Abbas Abdolmaleki, 2019, ICLR.

Meta-Learning Neural Bloom Filters

Sergey Bartunov, Jack W. Rae, Timothy Lillicrap, 2019, ICML.

Model-Free Episodic Control pdf

Joel Z. Leibo, Demis Hassabis, Yazhe Li, 2016, ArXiv.

Compressive Transformers for Long-Range Sequence Modelling pdf

Timothy P. Lillicrap, Siddhant M. Jayakumar, Anna Potapenko, 2019, ICLR.

Scaling Memory-Augmented Neural Networks with Sparse Reads and Writes

Alex Graves, Jonathan J. Hunt, Ivo Danihelka, 2016, NIPS.

Improving language models by retrieving from trillions of tokens pdf

Erich Elsen, Arthur Mensch, Simon Osindero, 2021, ArXiv.

Scaling Language Models: Methods, Analysis & Insights from Training Gopher pdf

Po-Sen Huang, Erich Elsen, Arthur Mensch, 2021, ArXiv.

A Clinically Applicable Approach to Continuous Prediction of Future Acute Kidney Injury

Suman V. Ravuri, Jack W. Rae, Ivan V. Protsyuk, 2019, Nature.

Developing Deep Learning Continuous Risk Models for Early Adverse Event Prediction in Electronic Health Records: an AKI Case Study

Geraint Rees, Demis Hassabis, Shakir Mohamed, 2019 .

EMORY-BASED P ARAMETER A DAPTATION

Adrià Puigdomènech Badia, Siddhant M. Jayakumar, Jack W. Rae, 2018 .

Developing Continuous Risk Models for Adverse Event Prediction in Electronic Health Records using Deep Learning

Suman V. Ravuri, Jack W. Rae, Thomas F. Osborne, 2020 .

Training Compute-Optimal Large Language Models

Lisa Anne Hendricks, Diego de Las Casas, Jack W. Rae, 2022, ArXiv.

Meta-Learning Deep Energy-Based Memory Models

Jack W. Rae, T. Lillicrap, Simon Osindero, 2019, ICLR.

Training Compute-Optimal Large Language Models

Lisa Anne Hendricks, Diego de Las Casas, Jack W. Rae, 2022, ArXiv.

Improving language models by retrieving from trillions of tokens

Diego de Las Casas, Jack W. Rae, George van den Driessche, 2021, ICML.

Use of deep learning to develop continuous-risk models for adverse event prediction from electronic health records

Suman V. Ravuri, Jack W. Rae, Ivan V. Protsyuk, 2021, Nature Protocols.

Unified Scaling Laws for Routed Language Models

Blake A. Hechtman, Diego de Las Casas, Jack W. Rae, 2022, ICML.

Reducing Sentiment Bias in Language Models via Counterfactual Evaluation

Po-Sen Huang, Pushmeet Kohli, Huan Zhang, 2019, FINDINGS.

An empirical analysis of compute-optimal large language model training

Lisa Anne Hendricks, Diego de Las Casas, Jack W. Rae, 2022, NeurIPS.

Do Transformers Need Deep Long-Range Memory?

Jack W. Rae, Jack Rae, Ali Razavi, 2020, ACL.

Meta-Learning Neural Bloom Filters

Jack W. Rae, T. Lillicrap, Sergey Bartunov, 2019, ICML.

Lesson learned on how to develop and deploy light-weight models in the era of humongous Language Models

Jack W. Rae, George van den Driessche, Dirk Groeneveld, 2022 .

Gemini: A Family of Highly Capable Multimodal Models

Tara N. Sainath, Dalia El Badawy, Reinald Kim Amplayo, 2023, ArXiv.