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11/11/2022
Efficient Deep Reinforcement Learning with Predictive Processing Proximal Policy Optimization
Advances in reinforcement learning (RL) often rely on massive compute re...
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06/24/2021
ChaLearn Looking at People: Inpainting and Denoising challenges
Dealing with incomplete information is a well studied problem in the con...
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06/29/2020
Explainable 3D Convolutional Neural Networks by Learning Temporal Transformations
In this paper we introduce the temporally factorized 3D convolution (3TC...
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01/29/2020
The Indian Chefs Process
This paper introduces the Indian Chefs Process (ICP), a Bayesian nonpara...
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12/20/2019
Background Hardly Matters: Understanding Personality Attribution in Deep Residual Networks
Perceived personality traits attributed to an individual do not have to ...
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12/09/2019
Temporal Factorization of 3D Convolutional Kernels
3D convolutional neural networks are difficult to train because they are...
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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...
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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...
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05/29/2018
Forward Amortized Inference for Likelihood-Free Variational Marginalization
In this paper, we introduce a new form of amortized variational inferenc...
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05/29/2018
Wasserstein Variational Inference
This paper introduces Wasserstein variational inference, a new form of a...
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04/21/2018
First Impressions: A Survey on Computer Vision-Based Apparent Personality Trait Analysis
Personality analysis has been widely studied in psychology, neuropsychol...
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02/02/2018
Explaining First Impressions: Modeling, Recognizing, and Explaining Apparent Personality from Videos
Explainability and interpretability are two critical aspects of decision...
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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...
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05/19/2017
Deep adversarial neural decoding
Here, we present a novel approach to solve the problem of reconstructing...
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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...
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02/17/2017
Estimating Nonlinear Dynamics with the ConvNet Smoother
Estimating the state of a dynamical system from a series of noise-corrup...
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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...
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06/09/2016
