Umut Güçlü | DeepAI

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Featured Co-authors

Sergio Escalera
71 publications
Isabelle Guyon
38 publications
Jun Wan
32 publications
François Laviolette
31 publications
Philippe Giguère
29 publications
Luca Ambrogioni
25 publications
Marcel van Gerven
22 publications
Hugo Jair Escalante
21 publications
Marcel A. J. van Gerven
18 publications
Meysam Madadi
14 publications
Brahim Chaib-draa
14 publications

∙ 11/11/2022

Efficient Deep Reinforcement Learning with Predictive Processing Proximal Policy Optimization

Advances in reinforcement learning (RL) often rely on massive compute re...

0 Burcu Küçükoğlu, et al. ∙

∙ 06/24/2021

ChaLearn Looking at People: Inpainting and Denoising challenges

Dealing with incomplete information is a well studied problem in the con...

28 Sergio Escalera, et al. ∙

∙ 06/29/2020

Explainable 3D Convolutional Neural Networks by Learning Temporal Transformations

In this paper we introduce the temporally factorized 3D convolution (3TC...

70 Gabrielle Ras, et al. ∙

∙ 01/29/2020

The Indian Chefs Process

This paper introduces the Indian Chefs Process (ICP), a Bayesian nonpara...

16 Patrick Dallaire, et al. ∙

∙ 12/20/2019

Background Hardly Matters: Understanding Personality Attribution in Deep Residual Networks

Perceived personality traits attributed to an individual do not have to ...

0 Gabrielle Ras, et al. ∙

∙ 12/09/2019

Temporal Factorization of 3D Convolutional Kernels

3D convolutional neural networks are difficult to train because they are...

0 Gabrielle Ras, et al. ∙

∙ 07/09/2019

k-GANs: Ensemble of Generative Models with Semi-Discrete Optimal Transport

Generative adversarial networks (GANs) are the state of the art in gener...

1 Luca Ambrogioni, et al. ∙

∙ 11/07/2018

Wasserstein Variational Gradient Descent: From Semi-Discrete Optimal Transport to Ensemble Variational Inference

Particle-based variational inference offers a flexible way of approximat...

0 Luca Ambrogioni, et al. ∙

∙ 05/29/2018

Forward Amortized Inference for Likelihood-Free Variational Marginalization

In this paper, we introduce a new form of amortized variational inferenc...

0 Luca Ambrogioni, et al. ∙

∙ 05/29/2018

Wasserstein Variational Inference

This paper introduces Wasserstein variational inference, a new form of a...

0 Luca Ambrogioni, et al. ∙

∙ 04/21/2018

First Impressions: A Survey on Computer Vision-Based Apparent Personality Trait Analysis

Personality analysis has been widely studied in psychology, neuropsychol...

0 Julio C. S. Jacques Junior, et al. ∙

∙ 02/02/2018

Explaining First Impressions: Modeling, Recognizing, and Explaining Apparent Personality from Videos

Explainability and interpretability are two critical aspects of decision...

0 Hugo Jair Escalante, et al. ∙

∙ 05/19/2017

The Kernel Mixture Network: A Nonparametric Method for Conditional Density Estimation of Continuous Random Variables

This paper introduces the kernel mixture network, a new method for nonpa...

0 Luca Ambrogioni, et al. ∙

∙ 05/19/2017

Deep adversarial neural decoding

Here, we present a novel approach to solve the problem of reconstructing...

0 Yağmur Güçlütürk, et al. ∙

∙ 03/09/2017

End-to-end semantic face segmentation with conditional random fields as convolutional, recurrent and adversarial networks

Recent years have seen a sharp increase in the number of related yet dis...

0 Umut Güçlü, et al. ∙

∙ 02/17/2017

Estimating Nonlinear Dynamics with the ConvNet Smoother

Estimating the state of a dynamical system from a series of noise-corrup...

0 Luca Ambrogioni, et al. ∙

∙ 09/16/2016

Deep Impression: Audiovisual Deep Residual Networks for Multimodal Apparent Personality Trait Recognition

Here, we develop an audiovisual deep residual network for multimodal app...

0 Yağmur Güçlütürk, et al. ∙

∙ 06/09/2016

Convolutional Sketch Inversion

In this paper, we use deep neural networks for inverting face sketches t...

0 Yağmur Güçlütürk, et al. ∙