activity
20162026
most citedThe neuroconnectionist research programme

24 citations · 76 across the 28 of their papers we have counts for

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Showing 2018Show all

6 papers · 1 filter

stat.ML2018

Wasserstein variational gradient descent: From semi-discrete optimal transport to ensemble variational inference

Luca Ambrogioni, Umut Guclu, Marcel van Gerven

Particle-based variational inference offers a flexible way of approximating complex posterior distributions with a set of particles. In this paper we introduce a new particle-based…

stat.ML2018

Forward Amortized Inference for Likelihood-Free Variational Marginalization

Luca Ambrogioni, Umut Güçlü, Julia Berezutskaya +5

In this paper, we introduce a new form of amortized variational inference by using the forward KL divergence in a joint-contrastive variational loss. The resulting forward amortize…

cs.CV2018

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

Julio C. S. Jacques Junior, Yağmur Güçlütürk, Marc Pérez +8

Personality analysis has been widely studied in psychology, neuropsychology, and signal processing fields, among others. From the past few years, it also became an attractive resea…

cs.AI2018

Explanation Methods in Deep Learning: Users, Values, Concerns and Challenges

Gabrielle Ras, Marcel van Gerven, Pim Haselager

Issues regarding explainable AI involve four components: users, laws & regulations, explanations and algorithms. Together these components provide a context in which explanation me…

stat.ML2018

Generalization of an Upper Bound on the Number of Nodes Needed to Achieve Linear Separability

Marjolein Troost, Katja Seeliger, Marcel van Gerven

An important issue in neural network research is how to choose the number of nodes and layers such as to solve a classification problem. We provide new intuitions based on earlier…

cs.CV2018

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

Hugo Jair Escalante, Heysem Kaya, Albert Ali Salah +14

Explainability and interpretability are two critical aspects of decision support systems. Within computer vision, they are critical in certain tasks related to human behavior analy…