Caglar Gulcehre

is this you? claim profile

∙ 0 followers
Google ∙ Université de Montréal

Research Scientist at DeepMind

Featured Co-authors

Yoshua Bengio
334 publications
Kyunghyun Cho
157 publications
Aaron Courville
112 publications
Fan Yang
87 publications
Pushmeet Kohli
83 publications
Oriol Vinyals
76 publications
Chris Dyer
72 publications
Nando de Freitas
68 publications
Nicolas Heess
67 publications
Razvan Pascanu
55 publications
Bowen Zhou
50 publications

Hyperparameter Selection for Offline Reinforcement Learning

Offline reinforcement learning (RL purely from logged data) is an import...
07/17/2020 ∙ by Tom Le Paine, et al. ∙ 30 ∙ share

read it
Critic Regularized Regression

Offline reinforcement learning (RL), also known as batch RL, offers the ...
06/26/2020 ∙ by Ziyu Wang, et al. ∙ 32 ∙ share

read it
RL Unplugged: Benchmarks for Offline Reinforcement Learning

Offline methods for reinforcement learning have the potential to help br...
06/24/2020 ∙ by Caglar Gulcehre, et al. ∙ 10 ∙ share

read it
Acme: A Research Framework for Distributed Reinforcement Learning

Deep reinforcement learning has led to many recent-and groundbreaking-ad...
06/01/2020 ∙ by Matt Hoffman, et al. ∙ 22 ∙ share

read it
Improving the Gating Mechanism of Recurrent Neural Networks

Gating mechanisms are widely used in neural network models, where they a...
10/22/2019 ∙ by Albert Gu, et al. ∙ 30 ∙ share

read it
Stabilizing Transformers for Reinforcement Learning

Owing to their ability to both effectively integrate information over lo...
10/13/2019 ∙ by Emilio Parisotto, et al. ∙ 7 ∙ share

read it
Making Efficient Use of Demonstrations to Solve Hard Exploration Problems

This paper introduces R2D3, an agent that makes efficient use of demonst...
09/03/2019 ∙ by Tom Le Paine, et al. ∙ 10 ∙ share

read it
Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning

We propose a unified mechanism for achieving coordination and communicat...
10/19/2018 ∙ by Natasha Jaques, et al. ∙ 0 ∙ share

read it
Intrinsic Social Motivation via Causal Influence in Multi-Agent RL

We derive a new intrinsic social motivation for multi-agent reinforcemen...
10/19/2018 ∙ by Natasha Jaques, et al. ∙ 0 ∙ share

read it
Sample Efficient Adaptive Text-to-Speech

We present a meta-learning approach for adaptive text-to-speech (TTS) wi...
09/27/2018 ∙ by Yutian Chen, et al. ∙ 2 ∙ share

read it
Relational inductive biases, deep learning, and graph networks

Artificial intelligence (AI) has undergone a renaissance recently, makin...
06/04/2018 ∙ by Peter W. Battaglia, et al. ∙ 0 ∙ share

read it
Hyperbolic Attention Networks

We introduce hyperbolic attention networks to endow neural networks with...
05/24/2018 ∙ by Caglar Gulcehre, et al. ∙ 0 ∙ share

read it
Plan, Attend, Generate: Planning for Sequence-to-Sequence Models

We investigate the integration of a planning mechanism into sequence-to-...
11/28/2017 ∙ by Francis Dutil, et al. ∙ 0 ∙ share

read it
Plan, Attend, Generate: Character-level Neural Machine Translation with Planning in the Decoder

We investigate the integration of a planning mechanism into an encoder-d...
06/13/2017 ∙ by Caglar Gulcehre, et al. ∙ 0 ∙ share

read it
Gated Orthogonal Recurrent Units: On Learning to Forget

We present a novel recurrent neural network (RNN) based model that combi...
06/08/2017 ∙ by Li Jing, et al. ∙ 0 ∙ share

read it
Machine Comprehension by Text-to-Text Neural Question Generation

We propose a recurrent neural model that generates natural-language ques...
05/04/2017 ∙ by Xingdi Yuan, et al. ∙ 0 ∙ share

read it
Memory Augmented Neural Networks with Wormhole Connections

Recent empirical results on long-term dependency tasks have shown that n...
01/30/2017 ∙ by Caglar Gulcehre, et al. ∙ 0 ∙ share

read it
Mollifying Networks

The optimization of deep neural networks can be more challenging than tr...
08/17/2016 ∙ by Caglar Gulcehre, et al. ∙ 0 ∙ share

read it
Dynamic Neural Turing Machine with Soft and Hard Addressing Schemes

We extend neural Turing machine (NTM) model into a dynamic neural Turing...
06/30/2016 ∙ by Caglar Gulcehre, 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
Pointing the Unknown Words

The problem of rare and unknown words is an important issue that can pot...
03/26/2016 ∙ by Caglar Gulcehre, et al. ∙ 0 ∙ share

read it
Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus

Over the past decade, large-scale supervised learning corpora have enabl...
03/22/2016 ∙ by Iulian Vlad Serban, et al. ∙ 0 ∙ share

read it
Noisy Activation Functions

Common nonlinear activation functions used in neural networks can cause ...
03/01/2016 ∙ by Caglar Gulcehre, et al. ∙ 0 ∙ share

read it
Abstractive Text Summarization Using Sequence-to-Sequence RNNs and Beyond

In this work, we model abstractive text summarization using Attentional ...
02/19/2016 ∙ by Ramesh Nallapati, et al. ∙ 0 ∙ share

read it
On Using Monolingual Corpora in Neural Machine Translation

Recent work on end-to-end neural network-based architectures for machine...
03/11/2015 ∙ by Caglar Gulcehre, 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
Gated Feedback Recurrent Neural Networks

In this work, we propose a novel recurrent neural network (RNN) architec...
02/09/2015 ∙ by Junyoung Chung, et al. ∙ 0 ∙ share

read it
ADASECANT: Robust Adaptive Secant Method for Stochastic Gradient

Stochastic gradient algorithms have been the main focus of large-scale l...
12/23/2014 ∙ by Caglar Gulcehre, et al. ∙ 0 ∙ share

read it
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

In this paper we compare different types of recurrent units in recurrent...
12/11/2014 ∙ by Junyoung Chung, et al. ∙ 0 ∙ share

read it
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation

In this paper, we propose a novel neural network model called RNN Encode...
06/03/2014 ∙ by Kyunghyun Cho, et al. ∙ 0 ∙ share

read it
How to Construct Deep Recurrent Neural Networks

In this paper, we explore different ways to extend a recurrent neural ne...
12/20/2013 ∙ by Razvan Pascanu, et al. ∙ 0 ∙ share

read it
Learned-Norm Pooling for Deep Feedforward and Recurrent Neural Networks

In this paper we propose and investigate a novel nonlinear unit, called ...
11/07/2013 ∙ by Caglar Gulcehre, et al. ∙ 0 ∙ share

read it
Knowledge Matters: Importance of Prior Information for Optimization

We explore the effect of introducing prior information into the intermed...
01/17/2013 ∙ by Caglar Gulcehre, et al. ∙ 0 ∙ share

read it