Pieter R. Roelfsema
Cognitive Neuroscience · 2000–2020
A researcher in the Science corpus: 9 papers; trusts 33 researchers and is trusted by 30 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 248 citations into it; #1,129 of 10,852 by trust here, #741 by citations
- Cellular and Molecular Neuroscience — 84 citations into it; #1,715 of 2,998 by trust here, #1,686 by citations
- Neuroscience — 38 citations into it; #119 of 487 by trust here, #118 by citations
- Artificial Intelligence — 33 citations into it
- Electrical and Electronic Engineering — 33 citations into it; #6,968 of 16,539 by trust here, #7,520 by citations
- Molecular Biology — 15 citations into it
- Developmental and Educational Psychology — 10 citations into it
- Experimental and Cognitive Psychology — 10 citations into it
Whom Pieter R. Roelfsema trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Michael L. Littman
- David E. Rumelhart
- Stanislas Dehaene
- Victor A. F. Lamme
- Giulio Tononi
- Ned Block
- Wolfram Schultz
- Gianluigi Mongillo
- Matthew E. Larkum
- Andrew Barto
Who trusts Pieter R. Roelfsema overall
- Guangyu Robert Yang
- Victor A. F. Lamme
- Wulfram Gerstner
- Alexandre Payeur
- Xiao-Jing Wang
- Elias H. Cohen
- Kristen A. Lindquist
- R. von der Heydt
- Stanislas Dehaene
- Johan Wagemans
Papers from Pieter R. Roelfsema's perspective
Ordered by how strongly the researchers Pieter R. Roelfsema trusts endorse each paper. Same corpus, a different order for every researcher.
- Reinforcement Learning: An Introduction
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- An integrative theory of prefrontal cortex function.
- Deep Learning
- Long Short-Term Memory
- Hierarchical models of object recognition in cortex
- Language Models are Unsupervised Multitask Learners
- Prototypical Networks for Few-shot Learning
Their papers
- Control of synaptic plasticity in deep cortical networks (2018) — 233 citations
- A deep learning framework for neuroscience (2019) — 1,016 citations
- The Brain's Router: A Cortical Network Model of Serial Processing in the Primate Brain (2010) — 131 citations
- Conscious Processing and the Global Neuronal Workspace Hypothesis (2020) — 894 citations
- The Distributed Nature of Working Memory. (2017) — 734 citations
- Alpha and gamma oscillations characterize feedback and feedforward processing in monkey visual cortex (2014) — 907 citations
- Different states in visual working memory: when it guides attention and when it does not. (2011) — 687 citations
- FigureGround Segregation in a Recurrent Network Architecture (2002) — 259 citations
- The distinct modes of vision offered by feedforward and recurrent processing. (2000) — 2,421 citations