Marcel van Gerven | DeepAI

AI Chat

Featured Co-authors

Pushmeet Kohli
93 publications
Irina Rish
51 publications
Philippe Giguère
32 publications
François Laviolette
31 publications
Luca Ambrogioni
25 publications
Guillermo Cecchi
25 publications
Pablo Lanillos
23 publications
Derek Doran
20 publications
Georg Langs
20 publications
Umut Güçlü
18 publications
Moritz Grosse-Wentrup
18 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. ∙

∙ 09/16/2022

Learning Policies for Continuous Control via Transition Models

It is doubtful that animals have perfect inverse models of their limbs (...

5 Justus Huebotter, et al. ∙

∙ 03/22/2022

Constrained Parameter Inference as a Principle for Learning

Learning in biological and artificial neural networks is often framed as...

0 Nasir Ahmad, et al. ∙

∙ 05/10/2021

Neuroscience-inspired perception-action in robotics: applying active inference for state estimation, control and self-perception

Unlike robots, humans learn, adapt and perceive their bodies by interact...

17 Pablo Lanillos, et al. ∙

∙ 02/23/2021

Scaling up learning with GAIT-prop

Backpropagation of error (BP) is a widely used and highly successful lea...

0 Sander Dalm, et al. ∙

∙ 02/09/2021

Automatic variational inference with cascading flows

The automation of probabilistic reasoning is one of the primary aims of ...

0 Luca Ambrogioni, et al. ∙

∙ 08/17/2020

A deep active inference model of the rubber-hand illusion

Understanding how perception and action deal with sensorimotor conflicts...

0 Thomas Rood, et al. ∙

∙ 04/30/2020

Explainable Deep Learning: A Field Guide for the Uninitiated

Deep neural network (DNN) is an indispensable machine learning tool for ...

23 Ning Xie, et al. ∙

∙ 03/17/2020

Virtual staining for mitosis detection in Breast Histopathology

We propose a virtual staining methodology based on Generative Adversaria...

0 Caner Mercan, et al. ∙

∙ 02/03/2020

Automatic structured variational inference

The aim of probabilistic programming is to automatize every aspect of pr...

0 Luca Ambrogioni, 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. ∙

∙ 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. ∙

∙ 03/25/2019

The functional role of cue-driven feature-based feedback in object recognition

Visual object recognition is not a trivial task, especially when the obj...

0 Sushrut Thorat, 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. ∙

∙ 03/20/2018

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

Issues regarding explainable AI involve four components: users, laws & r...

0 Gabrielle Ras, et al. ∙

∙ 02/10/2018

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

An important issue in neural network research is how to choose the numbe...

0 Marjolein Troost, 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. ∙

∙ 05/16/2017

GP CaKe: Effective brain connectivity with causal kernels

A fundamental goal in network neuroscience is to understand how activity...

0 Luca Ambrogioni, 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. ∙

∙ 01/06/2017

NIPS 2016 Workshop on Representation Learning in Artificial and Biological Neural Networks (MLINI 2016)

This workshop explores the interface between cognitive neuroscience and ...

0 Leila Wehbe, et al. ∙

∙ 10/12/2016

Deep disentangled representations for volumetric reconstruction

We introduce a convolutional neural network for inferring a compact dise...

0 Edward Grant, et al. ∙

∙ 12/04/2015

Predicting and visualizing psychological attributions with a deep neural network

Judgments about personality based on facial appearance are strong effect...

0 Edward Grant, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world