Alexandre de Brébisson | DeepAI

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∙ 10/08/2019

MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis

Previous works <cit.> have found that generating coherent raw audio wave...

0 Kundan Kumar, et al. ∙

∙ 01/20/2018

A Deep Reinforcement Learning Chatbot (Short Version)

We present MILABOT: a deep reinforcement learning chatbot developed by t...

0 Iulian V. Serban, et al. ∙

∙ 09/07/2017

A Deep Reinforcement Learning Chatbot

We present MILABOT: a deep reinforcement learning chatbot developed by t...

0 Iulian V. Serban, et al. ∙

∙ 09/19/2016

A Cheap Linear Attention Mechanism with Fast Lookups and Fixed-Size Representations

The softmax content-based attention mechanism has proven to be very bene...

0 Alexandre de Brébisson, et al. ∙

∙ 06/26/2016

Exact gradient updates in time independent of output size for the spherical loss family

An important class of problems involves training deep neural networks wi...

0 Pascal Vincent, et al. ∙

∙ 05/09/2016

Theano: A Python framework for fast computation of mathematical expressions

Theano is a Python library that allows to define, optimize, and evaluate...

0 The Theano Development Team, et al. ∙

∙ 04/29/2016

The Z-loss: a shift and scale invariant classification loss belonging to the Spherical Family

Despite being the standard loss function to train multi-class neural net...

0 Alexandre de Brébisson, et al. ∙

∙ 11/16/2015

An Exploration of Softmax Alternatives Belonging to the Spherical Loss Family

In a multi-class classification problem, it is standard to model the out...

0 Alexandre de Brébisson, et al. ∙

∙ 07/31/2015

Artificial Neural Networks Applied to Taxi Destination Prediction

We describe our first-place solution to the ECML/PKDD discovery challeng...

0 Alexandre de Brébisson, et al. ∙

∙ 02/09/2015

Deep Neural Networks for Anatomical Brain Segmentation

We present a novel approach to automatically segment magnetic resonance ...

0 Alexandre de Brébisson, et al. ∙

∙ 12/22/2014

Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets

An important class of problems involves training deep neural networks wi...

0 Pascal Vincent, et al. ∙

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