Christopher Pal

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Corporation de l'ecole Polytechnique de Montreal

Associate Professor at École Polytechnique de Montréal

Real-Time Reinforcement Learning

Markov Decision Processes (MDPs), the mathematical framework underlying ...
11/11/2019 ∙ by Simon Ramstedt, et al. ∙ 45 ∙ share

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Recurrent Transition Networks for Character Locomotion

Manually authoring transition animations for a complete locomotion syste...
10/04/2018 ∙ by Félix G. Harvey, et al. ∙ 16 ∙ share

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Dataflow-based Joint Quantization of Weights and Activations for Deep Neural Networks

This paper addresses a challenging problem - how to reduce energy consum...
01/04/2019 ∙ by Xue Geng, et al. ∙ 14 ∙ share

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Adversarial Mixup Resynthesizers

In this paper, we explore new approaches to combining information encode...
03/07/2019 ∙ by Christopher Beckham, et al. ∙ 12 ∙ share

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Towards Understanding Generalization in Gradient-Based Meta-Learning

In this work we study generalization of neural networks in gradient-base...
07/16/2019 ∙ by Simon Guiroy, et al. ∙ 9 ∙ share

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Neural Multisensory Scene Inference

For embodied agents to infer representations of the underlying 3D physic...
10/06/2019 ∙ by Jae Hyun Lim, et al. ∙ 7 ∙ share

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Interactive Machine Comprehension with Information Seeking Agents

Existing machine reading comprehension (MRC) models do not scale effecti...
08/27/2019 ∙ by Xingdi Yuan, et al. ∙ 5 ∙ share

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Supervise Thyself: Examining Self-Supervised Representations in Interactive Environments

Self-supervised methods, wherein an agent learns representations solely ...
06/27/2019 ∙ by Evan Racah, et al. ∙ 4 ∙ share

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Do Neural Dialog Systems Use the Conversation History Effectively? An Empirical Study

Neural generative models have been become increasingly popular when buil...
06/04/2019 ∙ by Chinnadhurai Sankar, et al. ∙ 2 ∙ share

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Recombinator Networks: Learning Coarse-to-Fine Feature Aggregation

Deep neural networks with alternating convolutional, max-pooling and dec...
11/23/2015 ∙ by Sina Honari, et al. ∙ 0 ∙ share

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Improving Landmark Localization with Semi-Supervised Learning

We present two techniques to improve landmark localization from partiall...
09/05/2017 ∙ by Sina Honari, et al. ∙ 0 ∙ share

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Unimodal probability distributions for deep ordinal classification

Probability distributions produced by the cross-entropy loss for ordinal...
05/15/2017 ∙ by Christopher Beckham, et al. ∙ 0 ∙ share

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A step towards procedural terrain generation with GANs

Procedural terrain generation for video games has been traditionally bee...
07/11/2017 ∙ by Christopher Beckham, et al. ∙ 0 ∙ share

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ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events

Then detection and identification of extreme weather events in large-sca...
12/07/2016 ∙ by Evan Racah, et al. ∙ 0 ∙ share

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A dataset and exploration of models for understanding video data through fill-in-the-blank question-answering

While deep convolutional neural networks frequently approach or exceed h...
11/23/2016 ∙ by Tegan Maharaj, et al. ∙ 0 ∙ share

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Convolutional Residual Memory Networks

Very deep convolutional neural networks (CNNs) yield state of the art re...
06/16/2016 ∙ by Joel Moniz, et al. ∙ 0 ∙ share

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EmoNets: Multimodal deep learning approaches for emotion recognition in video

The task of the emotion recognition in the wild (EmotiW) Challenge is to...
03/05/2015 ∙ by Samira Ebrahimi Kahou, et al. ∙ 0 ∙ share

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Using Descriptive Video Services to Create a Large Data Source for Video Annotation Research

In this work, we introduce a dataset of video annotated with high qualit...
03/03/2015 ∙ by Atousa Torabi, et al. ∙ 0 ∙ share

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Adversarial Generation of Natural Language

Generative Adversarial Networks (GANs) have gathered a lot of attention ...
05/31/2017 ∙ by Sai Rajeswar, et al. ∙ 0 ∙ share

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Movie Description

Audio Description (AD) provides linguistic descriptions of movies and al...
05/12/2016 ∙ by Anna Rohrbach, et al. ∙ 0 ∙ share

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Describing Videos by Exploiting Temporal Structure

Recent progress in using recurrent neural networks (RNNs) for image desc...
02/27/2015 ∙ by Li Yao, et al. ∙ 0 ∙ share

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Unsupervised Depth Estimation, 3D Face Rotation and Replacement

We present an unsupervised approach for learning to estimate three dimen...
03/25/2018 ∙ by Joel Ruben Antony Moniz, et al. ∙ 0 ∙ share

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Theano: A Python framework for fast computation of mathematical expressions

Theano is a Python library that allows to define, optimize, and evaluate...
05/09/2016 ∙ by The Theano Development Team, et al. ∙ 0 ∙ share

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A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms

We propose to meta-learn causal structures based on how fast a learner a...
01/30/2019 ∙ by Yoshua Bengio, et al. ∙ 0 ∙ share

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Interactive Language Learning by Question Answering

Humans observe and interact with the world to acquire knowledge. However...
08/28/2019 ∙ by Xingdi Yuan, et al. ∙ 0 ∙ share

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On Extractive and Abstractive Neural Document Summarization with Transformer Language Models

We present a method to produce abstractive summaries of long documents t...
09/07/2019 ∙ by Sandeep Subramanian, et al. ∙ 0 ∙ share

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Promoting Coordination through Policy Regularization in Multi-Agent Reinforcement Learning

A central challenge in multi-agent reinforcement learning is the inducti...
08/06/2019 ∙ by Paul Barde, et al. ∙ 0 ∙ share

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On the impressive performance of randomly weighted encoders in summarization tasks

In this work, we investigate the performance of untrained randomly initi...
02/21/2020 ∙ by Jonathan Pilault, et al. ∙ 0 ∙ share

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Christopher Pal

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