51 citations · 71 across the 4 of their papers we have counts for
7 papers
Learning Coordinated Terrain-Adaptive Locomotion by Imitating a Centroidal Dynamics Planner
Philemon Brakel, Steven Bohez, Leonard Hasenclever +2
Dynamic quadruped locomotion over challenging terrains with precise foot placements is a hard problem for both optimal control methods and Reinforcement Learning (RL). Non-linear s…
Recall Traces: Backtracking Models for Efficient Reinforcement Learning
Anirudh Goyal, Philemon Brakel, William Fedus +5
In many environments only a tiny subset of all states yield high reward. In these cases, few of the interactions with the environment provide a relevant learning signal. Hence, we…
Light Gated Recurrent Units for Speech Recognition
Mirco Ravanelli, Philemon Brakel, Maurizio Omologo +1
A field that has directly benefited from the recent advances in deep learning is Automatic Speech Recognition (ASR). Despite the great achievements of the past decades, however, a…
Learning Independent Features with Adversarial Nets for Non-linear ICA
Philemon Brakel, Yoshua Bengio
Reliable measures of statistical dependence could be useful tools for learning independent features and performing tasks like source separation using Independent Component Analysis…
Improving speech recognition by revising gated recurrent units
Mirco Ravanelli, Philemon Brakel, Maurizio Omologo +1
Speech recognition is largely taking advantage of deep learning, showing that substantial benefits can be obtained by modern Recurrent Neural Networks (RNNs). The most popular RNNs…
Batch-normalized joint training for DNN-based distant speech recognition
Mirco Ravanelli, Philemon Brakel, Maurizio Omologo +1
Improving distant speech recognition is a crucial step towards flexible human-machine interfaces. Current technology, however, still exhibits a lack of robustness, especially when…