Philemon Brakel

Affiliations:
  • Google DeepMind, London, UK
  • University of Montreal, Department of Computer Science and Operations Research, QC, Canada


According to our database1, Philemon Brakel authored at least 23 papers between 2011 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Offline Actor-Critic Reinforcement Learning Scales to Large Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2022
Imitate and Repurpose: Learning Reusable Robot Movement Skills From Human and Animal Behaviors.
CoRR, 2022

Learning Coordinated Terrain-Adaptive Locomotion by Imitating a Centroidal Dynamics Planner.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

2021
A Constrained Multi-Objective Reinforcement Learning Framework.
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2019
Recall Traces: Backtracking Models for Efficient Reinforcement Learning.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Light Gated Recurrent Units for Speech Recognition.
IEEE Trans. Emerg. Top. Comput. Intell., 2018

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

2017
Improving Speech Recognition by Revising Gated Recurrent Units.
Proceedings of the 18th Annual Conference of the International Speech Communication Association, 2017

An Actor-Critic Algorithm for Sequence Prediction.
Proceedings of the 5th International Conference on Learning Representations, 2017

A network of deep neural networks for Distant Speech Recognition.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2016
Invariant Representations for Noisy Speech Recognition.
CoRR, 2016

Batch-normalized joint training for DNN-based distant speech recognition.
Proceedings of the 2016 IEEE Spoken Language Technology Workshop, 2016

Towards End-to-End Speech Recognition with Deep Convolutional Neural Networks.
Proceedings of the 17th Annual Conference of the International Speech Communication Association, 2016

Deconstructing the Ladder Network Architecture.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Batch normalized recurrent neural networks.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

End-to-end attention-based large vocabulary speech recognition.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

2015
Task Loss Estimation for Sequence Prediction.
CoRR, 2015

2013
Training energy-based models for time-series imputation.
J. Mach. Learn. Res., 2013

Bidirectional truncated recurrent neural networks for efficient speech denoising.
Proceedings of the 14th Annual Conference of the International Speech Communication Association, 2013

2012
Oger: modular learning architectures for large-scale sequential processing.
J. Mach. Learn. Res., 2012

Energy-Based Temporal Neural Networks for Imputing Missing Values.
Proceedings of the Neural Information Processing - 19th International Conference, 2012

Training Restricted Boltzmann Machines with Multi-tempering: Harnessing Parallelization.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2012, 2012

2011
Audio-based Music Classification with a Pretrained Convolutional Network.
Proceedings of the 12th International Society for Music Information Retrieval Conference, 2011


  Loading...