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Going in circles is the way forward: the role of recurrence in visual
  inference

Going in circles is the way forward: the role of recurrence in visual inference

26 March 2020
R. S. V. Bergen
N. Kriegeskorte
ArXivPDFHTML

Papers citing "Going in circles is the way forward: the role of recurrence in visual inference"

27 / 27 papers shown
Title
Multimodal Visual-haptic pose estimation in the presence of transient
  occlusion
Multimodal Visual-haptic pose estimation in the presence of transient occlusion
Michael Zechmair
Yannick Morel
24
0
0
27 Jun 2024
Spiking representation learning for associative memories
Spiking representation learning for associative memories
Naresh B. Ravichandran
A. Lansner
Pawel Herman
29
1
0
05 Jun 2024
Zamba: A Compact 7B SSM Hybrid Model
Zamba: A Compact 7B SSM Hybrid Model
Paolo Glorioso
Quentin G. Anthony
Yury Tokpanov
James Whittington
Jonathan Pilault
Adam Ibrahim
Beren Millidge
25
45
0
26 May 2024
ProcNet: Deep Predictive Coding Model for Robust-to-occlusion Visual
  Segmentation and Pose Estimation
ProcNet: Deep Predictive Coding Model for Robust-to-occlusion Visual Segmentation and Pose Estimation
Michael Zechmair
Alban Bornet
Yannick Morel
6
0
0
27 Oct 2023
Dynamic Early Exiting Predictive Coding Neural Networks
Dynamic Early Exiting Predictive Coding Neural Networks
Alaa Zniber
Ouassim Karrakchou
Mounir Ghogho
17
0
0
05 Sep 2023
GPTEval: A Survey on Assessments of ChatGPT and GPT-4
GPTEval: A Survey on Assessments of ChatGPT and GPT-4
Rui Mao
Guanyi Chen
Xulang Zhang
Frank Guerin
Erik Cambria
ELM
LM&MA
28
100
0
24 Aug 2023
Characterising representation dynamics in recurrent neural networks for
  object recognition
Characterising representation dynamics in recurrent neural networks for object recognition
Sushrut Thorat
Adrien Doerig
Tim C Kietzmann
12
2
0
23 Aug 2023
Are Deep Neural Networks Adequate Behavioural Models of Human Visual
  Perception?
Are Deep Neural Networks Adequate Behavioural Models of Human Visual Perception?
Felix Wichmann
Robert Geirhos
25
25
0
26 May 2023
Bio-Inspired, Task-Free Continual Learning through Activity
  Regularization
Bio-Inspired, Task-Free Continual Learning through Activity Regularization
Francesco Lassig
Pau Vilimelis Aceituno
M. Sorbaro
Benjamin Grewe
CLL
20
8
0
08 Dec 2022
The least-control principle for local learning at equilibrium
The least-control principle for local learning at equilibrium
Alexander Meulemans
Nicolas Zucchet
Seijin Kobayashi
J. Oswald
João Sacramento
20
19
0
04 Jul 2022
Brain-like combination of feedforward and recurrent network components
  achieves prototype extraction and robust pattern recognition
Brain-like combination of feedforward and recurrent network components achieves prototype extraction and robust pattern recognition
Naresh B. Ravichandran
A. Lansner
Pawel Herman
19
4
0
30 Jun 2022
Hybrid Predictive Coding: Inferring, Fast and Slow
Hybrid Predictive Coding: Inferring, Fast and Slow
Alexander Tschantz
Beren Millidge
A. Seth
Christopher L. Buckley
19
36
0
05 Apr 2022
Recent Advances in Neural Text Generation: A Task-Agnostic Survey
Recent Advances in Neural Text Generation: A Task-Agnostic Survey
Chen Tang
Frank Guerin
Chenghua Lin
AI4CE
OOD
28
19
0
06 Mar 2022
Data-driven emergence of convolutional structure in neural networks
Data-driven emergence of convolutional structure in neural networks
Alessandro Ingrosso
Sebastian Goldt
48
38
0
01 Feb 2022
Recur, Attend or Convolve? On Whether Temporal Modeling Matters for
  Cross-Domain Robustness in Action Recognition
Recur, Attend or Convolve? On Whether Temporal Modeling Matters for Cross-Domain Robustness in Action Recognition
Sofia Broomé
Ernest Pokropek
Boyu Li
Hedvig Kjellström
13
7
0
22 Dec 2021
Category-orthogonal object features guide information processing in
  recurrent neural networks trained for object categorization
Category-orthogonal object features guide information processing in recurrent neural networks trained for object categorization
Sushrut Thorat
G. Aldegheri
Tim C Kietzmann
12
11
0
15 Nov 2021
Recurrent Attention Models with Object-centric Capsule Representation
  for Multi-object Recognition
Recurrent Attention Models with Object-centric Capsule Representation for Multi-object Recognition
Hossein Adeli
Seoyoung Ahn
G. Zelinsky
OCL
23
3
0
11 Oct 2021
Capturing the objects of vision with neural networks
Capturing the objects of vision with neural networks
B. Peters
N. Kriegeskorte
OCL
18
56
0
07 Sep 2021
Layer Folding: Neural Network Depth Reduction using Activation
  Linearization
Layer Folding: Neural Network Depth Reduction using Activation Linearization
Amir Ben Dror
Niv Zehngut
Avraham Raviv
E. Artyomov
Ran Vitek
R. Jevnisek
13
20
0
17 Jun 2021
Projection: A Mechanism for Human-like Reasoning in Artificial
  Intelligence
Projection: A Mechanism for Human-like Reasoning in Artificial Intelligence
Frank Guerin
35
4
0
24 Mar 2021
Hybrid Backpropagation Parallel Reservoir Networks
Hybrid Backpropagation Parallel Reservoir Networks
Matthew Evanusa
Snehesh Shrestha
M. Girvan
Cornelia Fermuller
Yiannis Aloimonos
AI4TS
20
0
0
27 Oct 2020
Seeing eye-to-eye? A comparison of object recognition performance in
  humans and deep convolutional neural networks under image manipulation
Seeing eye-to-eye? A comparison of object recognition performance in humans and deep convolutional neural networks under image manipulation
Leonard E. van Dyck
W. Gruber
9
3
0
13 Jul 2020
Beyond accuracy: quantifying trial-by-trial behaviour of CNNs and humans
  by measuring error consistency
Beyond accuracy: quantifying trial-by-trial behaviour of CNNs and humans by measuring error consistency
Robert Geirhos
Kristof Meding
Felix Wichmann
6
116
0
30 Jun 2020
Hierarchically Compositional Tasks and Deep Convolutional Networks
Hierarchically Compositional Tasks and Deep Convolutional Networks
Arturo Deza
Q. Liao
Andrzej Banburski
T. Poggio
BDL
OOD
17
2
0
24 Jun 2020
Learning Physical Graph Representations from Visual Scenes
Learning Physical Graph Representations from Visual Scenes
Daniel M. Bear
Chaofei Fan
Damian Mrowca
Yunzhu Li
S. Alter
...
Jeremy Schwartz
Li Fei-Fei
Jiajun Wu
J. Tenenbaum
Daniel L. K. Yamins
SSL
GNN
SSeg
AI4CE
35
78
0
22 Jun 2020
Five Points to Check when Comparing Visual Perception in Humans and
  Machines
Five Points to Check when Comparing Visual Perception in Humans and Machines
Christina M. Funke
Judy Borowski
Karolina Stosio
Wieland Brendel
Thomas S. A. Wallis
Matthias Bethge
12
33
0
20 Apr 2020
Bridging the Gaps Between Residual Learning, Recurrent Neural Networks
  and Visual Cortex
Bridging the Gaps Between Residual Learning, Recurrent Neural Networks and Visual Cortex
Q. Liao
T. Poggio
206
255
0
13 Apr 2016
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