Christopher Pal

is this you? claim profile

∙ 0 followers
Corporation de l'ecole Polytechnique de Montreal

Associate Professor at École Polytechnique de Montréal

Latent Variable Nested Set Transformers AutoBots

Humans have the innate ability to attend to the most relevant actors in ...
02/19/2021 ∙ by Roger Girgis, et al. ∙ 0 ∙ share

read it
Robust Motion In-betweening

In this work we present a novel, robust transition generation technique ...
02/09/2021 ∙ by Félix G. Harvey, et al. ∙ 12 ∙ share

read it
Learning to Summarize Long Texts with Memory Compression and Transfer

We introduce Mem2Mem, a memory-to-memory mechanism for hierarchical recu...
10/21/2020 ∙ by Jaehong Park, et al. ∙ 0 ∙ share

read it
Reinforcement Learning with Random Delays

Action and observation delays commonly occur in many Reinforcement Learn...
10/06/2020 ∙ by Simon Ramstedt, et al. ∙ 0 ∙ share

read it
Measuring Systematic Generalization in Neural Proof Generation with Transformers

We are interested in understanding how well Transformer language models ...
09/30/2020 ∙ by Nicolas Gontier, et al. ∙ 6 ∙ share

read it
Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters Less Data

Multi-Task Learning (MTL) has emerged as a promising approach for transf...
09/19/2020 ∙ by Jonathan Pilault, et al. ∙ 7 ∙ share

read it
Action-Based Representation Learning for Autonomous Driving

Human drivers produce a vast amount of data which could, in principle, b...
08/21/2020 ∙ by Yi Xiao, et al. ∙ 9 ∙ share

read it
Adversarial Soft Advantage Fitting: Imitation Learning without Policy Optimization

Adversarial imitation learning alternates between learning a discriminat...
06/23/2020 ∙ by Paul Barde, et al. ∙ 15 ∙ share

read it
AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation

Entropy is ubiquitous in machine learning, but it is in general intracta...
06/09/2020 ∙ by Jae Hyun Lim, et al. ∙ 12 ∙ share

read it
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

read it
Real-Time Reinforcement Learning

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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
Adversarial Mixup Resynthesizers

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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
Movie Description

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

read it
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

read it
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

read it
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

read it
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

read it
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

read it

Christopher Pal

Featured Co-authors