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Decoupled Neural Interfaces using Synthetic Gradients
v1v2 (latest)

Decoupled Neural Interfaces using Synthetic Gradients

18 August 2016
Max Jaderberg
Wojciech M. Czarnecki
Simon Osindero
Oriol Vinyals
Alex Graves
David Silver
Koray Kavukcuoglu
ArXiv (abs)PDFHTML

Papers citing "Decoupled Neural Interfaces using Synthetic Gradients"

50 / 212 papers shown
Title
Convolutional Neural Generative Coding: Scaling Predictive Coding to
  Natural Images
Convolutional Neural Generative Coding: Scaling Predictive Coding to Natural Images
Alexander Ororbia
A. Mali
BDL
70
11
0
22 Nov 2022
Scaling Laws Beyond Backpropagation
Scaling Laws Beyond Backpropagation
Matthew J. Filipovich
Alessandro Cappelli
Daniel Hesslow
Julien Launay
55
3
0
26 Oct 2022
Block-wise Training of Residual Networks via the Minimizing Movement
  Scheme
Block-wise Training of Residual Networks via the Minimizing Movement Scheme
Skander Karkar
Ibrahim Ayed
Emmanuel de Bézenac
Patrick Gallinari
70
1
0
03 Oct 2022
Hebbian Deep Learning Without Feedback
Hebbian Deep Learning Without Feedback
Adrien Journé
Hector Garcia Rodriguez
Qinghai Guo
Timoleon Moraitis
AAML
91
54
0
23 Sep 2022
Active Predicting Coding: Brain-Inspired Reinforcement Learning for
  Sparse Reward Robotic Control Problems
Active Predicting Coding: Brain-Inspired Reinforcement Learning for Sparse Reward Robotic Control Problems
Alexander Ororbia
A. Mali
93
8
0
19 Sep 2022
Biologically Plausible Training of Deep Neural Networks Using a Top-down
  Credit Assignment Network
Biologically Plausible Training of Deep Neural Networks Using a Top-down Credit Assignment Network
Jian-Hui Chen
Cheng-Lin Liu
Zuoren Wang
55
0
0
01 Aug 2022
Layer-Wise Partitioning and Merging for Efficient and Scalable Deep
  Learning
Layer-Wise Partitioning and Merging for Efficient and Scalable Deep Learning
S. Akintoye
Liangxiu Han
H. Lloyd
Xin Zhang
Darren Dancey
Haoming Chen
Daoqiang Zhang
FedML
90
5
0
22 Jul 2022
GLEAM: Greedy Learning for Large-Scale Accelerated MRI Reconstruction
GLEAM: Greedy Learning for Large-Scale Accelerated MRI Reconstruction
Batu Mehmet Ozturkler
Arda Sahiner
Tolga Ergen
Arjun D Desai
Christopher M. Sandino
S. Vasanawala
John M. Pauly
Morteza Mardani
Mert Pilanci
55
4
0
18 Jul 2022
Emergent Abilities of Large Language Models
Emergent Abilities of Large Language Models
Jason W. Wei
Yi Tay
Rishi Bommasani
Colin Raffel
Barret Zoph
...
Tatsunori Hashimoto
Oriol Vinyals
Percy Liang
J. Dean
W. Fedus
ELMReLMLRM
322
2,526
0
15 Jun 2022
A Robust Backpropagation-Free Framework for Images
A Robust Backpropagation-Free Framework for Images
Timothy Zee
Alexander Ororbia
A. Mali
Ifeoma Nwogu
56
1
0
03 Jun 2022
BackLink: Supervised Local Training with Backward Links
BackLink: Supervised Local Training with Backward Links
Wenzhe Guo
M. Fouda
A. Eltawil
K. Salama
50
2
0
14 May 2022
Signal Propagation: A Framework for Learning and Inference In a Forward
  Pass
Signal Propagation: A Framework for Learning and Inference In a Forward Pass
Adam A. Kohan
E. Rietman
H. Siegelmann
77
27
0
04 Apr 2022
The Frost Hollow Experiments: Pavlovian Signalling as a Path to
  Coordination and Communication Between Agents
The Frost Hollow Experiments: Pavlovian Signalling as a Path to Coordination and Communication Between Agents
P. Pilarski
Andrew Butcher
Elnaz Davoodi
Michael Bradley Johanson
Dylan J. A. Brenneis
Adam S. R. Parker
Leslie Acker
M. Botvinick
Joseph Modayil
Adam White
AI4CE
54
4
0
17 Mar 2022
Gradient Correction beyond Gradient Descent
Zefan Li
Bingbing Ni
Teng Li
WenJun Zhang
Wen Gao
26
0
0
16 Mar 2022
MetAug: Contrastive Learning via Meta Feature Augmentation
MetAug: Contrastive Learning via Meta Feature Augmentation
Jiangmeng Li
Jingyao Wang
Changwen Zheng
Fuchun Sun
Hui Xiong
94
24
0
10 Mar 2022
Efficient Attribute Unlearning: Towards Selective Removal of Input
  Attributes from Feature Representations
Efficient Attribute Unlearning: Towards Selective Removal of Input Attributes from Feature Representations
Tao Guo
Song Guo
Jiewei Zhang
Wenchao Xu
Junxiao Wang
MU
79
18
0
27 Feb 2022
Gradients without Backpropagation
Gradients without Backpropagation
A. G. Baydin
Barak A. Pearlmutter
Don Syme
Frank Wood
Philip Torr
82
67
0
17 Feb 2022
Error-driven Input Modulation: Solving the Credit Assignment Problem
  without a Backward Pass
Error-driven Input Modulation: Solving the Credit Assignment Problem without a Backward Pass
Giorgia Dellaferrera
Gabriel Kreiman
80
56
0
27 Jan 2022
Learning to Predict Gradients for Semi-Supervised Continual Learning
Learning to Predict Gradients for Semi-Supervised Continual Learning
Yan Luo
Yongkang Wong
Mohan S. Kankanhalli
Qi Zhao
SSLCLL
70
8
0
23 Jan 2022
Neural Capacitance: A New Perspective of Neural Network Selection via
  Edge Dynamics
Neural Capacitance: A New Perspective of Neural Network Selection via Edge Dynamics
Chunheng Jiang
Tejaswini Pedapati
Pin-Yu Chen
Yizhou Sun
Jianxi Gao
70
2
0
11 Jan 2022
Layer-Parallel Training of Residual Networks with Auxiliary-Variable
  Networks
Layer-Parallel Training of Residual Networks with Auxiliary-Variable Networks
Qi Sun
Hexin Dong
Zewei Chen
Jiacheng Sun
Zhenguo Li
Bin Dong
68
2
0
10 Dec 2021
Target Propagation via Regularized Inversion
Target Propagation via Regularized Inversion
Vincent Roulet
Zaïd Harchaoui
BDLAAML
93
4
0
02 Dec 2021
On Training Implicit Models
On Training Implicit Models
Zhengyang Geng
Xinyu Zhang
Shaojie Bai
Yisen Wang
Zhouchen Lin
127
72
0
09 Nov 2021
Cortico-cerebellar networks as decoupling neural interfaces
Cortico-cerebellar networks as decoupling neural interfaces
J. Pemberton
E. Boven
Richard Apps
Rui Ponte Costa
70
6
0
21 Oct 2021
Biologically Plausible Training Mechanisms for Self-Supervised Learning
  in Deep Networks
Biologically Plausible Training Mechanisms for Self-Supervised Learning in Deep Networks
Mufeng Tang
Yibo Yang
Y. Amit
SSL
138
7
0
30 Sep 2021
LayerPipe: Accelerating Deep Neural Network Training by Intra-Layer and
  Inter-Layer Gradient Pipelining and Multiprocessor Scheduling
LayerPipe: Accelerating Deep Neural Network Training by Intra-Layer and Inter-Layer Gradient Pipelining and Multiprocessor Scheduling
Nanda K. Unnikrishnan
Keshab K. Parhi
AI4CE
37
6
0
14 Aug 2021
Knowledge accumulating: The general pattern of learning
Knowledge accumulating: The general pattern of learning
Zhuoran Xu
Hao Liu
CLL
74
0
0
09 Aug 2021
Few-Shot and Continual Learning with Attentive Independent Mechanisms
Few-Shot and Continual Learning with Attentive Independent Mechanisms
Eugene Lee
Cheng-Han Huang
Chen-Yi Lee
CLL
60
25
0
29 Jul 2021
Backprop-Free Reinforcement Learning with Active Neural Generative
  Coding
Backprop-Free Reinforcement Learning with Active Neural Generative Coding
Alexander Ororbia
A. Mali
92
17
0
10 Jul 2021
Decoupled Greedy Learning of CNNs for Synchronous and Asynchronous
  Distributed Learning
Decoupled Greedy Learning of CNNs for Synchronous and Asynchronous Distributed Learning
Eugene Belilovsky
Louis Leconte
Lucas Caccia
Michael Eickenberg
Edouard Oyallon
45
7
0
11 Jun 2021
LocoProp: Enhancing BackProp via Local Loss Optimization
LocoProp: Enhancing BackProp via Local Loss Optimization
Ehsan Amid
Rohan Anil
Manfred K. Warmuth
ODL
56
20
0
11 Jun 2021
Front Contribution instead of Back Propagation
Front Contribution instead of Back Propagation
Swaroop Mishra
Anjana Arunkumar
42
0
0
10 Jun 2021
Bottom-up and top-down approaches for the design of neuromorphic
  processing systems: Tradeoffs and synergies between natural and artificial
  intelligence
Bottom-up and top-down approaches for the design of neuromorphic processing systems: Tradeoffs and synergies between natural and artificial intelligence
Charlotte Frenkel
D. Bol
Giacomo Indiveri
85
36
0
02 Jun 2021
Prediction of the Position of External Markers Using a Recurrent Neural
  Network Trained With Unbiased Online Recurrent Optimization for Safe Lung
  Cancer Radiotherapy
Prediction of the Position of External Markers Using a Recurrent Neural Network Trained With Unbiased Online Recurrent Optimization for Safe Lung Cancer Radiotherapy
Michel Pohl
Mitsuru Uesaka
Hiroyuki Takahashi
K. Demachi
R. B. Chhatkuli
67
7
0
02 Jun 2021
Current State and Future Directions for Learning in Biological Recurrent
  Neural Networks: A Perspective Piece
Current State and Future Directions for Learning in Biological Recurrent Neural Networks: A Perspective Piece
Luke Y. Prince
Roy Henha Eyono
E. Boven
Arna Ghosh
Joe Pemberton
...
Rui Ponte Costa
Wolfgang Maass
Blake A. Richards
Cristina Savin
K. Wilmes
CLL
42
4
0
12 May 2021
Perceptual Gradient Networks
Perceptual Gradient Networks
Dmitry Nikulin
Roman Suvorov
Aleksei Ivakhnenko
Victor Lempitsky
37
0
0
05 May 2021
Local Critic Training for Model-Parallel Learning of Deep Neural
  Networks
Local Critic Training for Model-Parallel Learning of Deep Neural Networks
Hojung Lee
Cho-Jui Hsieh
Jong-Seok Lee
63
15
0
03 Feb 2021
Revisiting Locally Supervised Learning: an Alternative to End-to-end
  Training
Revisiting Locally Supervised Learning: an Alternative to End-to-end Training
Yulin Wang
Zanlin Ni
Shiji Song
Le Yang
Gao Huang
72
85
0
26 Jan 2021
Training Deep Architectures Without End-to-End Backpropagation: A Survey
  on the Provably Optimal Methods
Training Deep Architectures Without End-to-End Backpropagation: A Survey on the Provably Optimal Methods
Shiyu Duan
José C. Príncipe
MQ
102
3
0
09 Jan 2021
Advances in Electron Microscopy with Deep Learning
Advances in Electron Microscopy with Deep Learning
Jeffrey M. Ede
115
3
0
04 Jan 2021
Differentiable Programming à la Moreau
Differentiable Programming à la Moreau
Vincent Roulet
Zaïd Harchaoui
81
5
0
31 Dec 2020
Reservoir Transformers
Reservoir Transformers
Sheng Shen
Alexei Baevski
Ari S. Morcos
Kurt Keutzer
Michael Auli
Douwe Kiela
97
18
0
30 Dec 2020
Hardware Beyond Backpropagation: a Photonic Co-Processor for Direct
  Feedback Alignment
Hardware Beyond Backpropagation: a Photonic Co-Processor for Direct Feedback Alignment
Julien Launay
Iacopo Poli
Kilian Muller
Gustave Pariente
I. Carron
L. Daudet
Florent Krzakala
S. Gigan
MoE
75
18
0
11 Dec 2020
Parallel Training of Deep Networks with Local Updates
Parallel Training of Deep Networks with Local Updates
Michael Laskin
Luke Metz
Seth Nabarrao
Mark Saroufim
Badreddine Noune
Carlo Luschi
Jascha Narain Sohl-Dickstein
Pieter Abbeel
FedML
122
27
0
07 Dec 2020
The Neural Coding Framework for Learning Generative Models
The Neural Coding Framework for Learning Generative Models
Alexander Ororbia
Daniel Kifer
GAN
104
68
0
07 Dec 2020
Accumulated Decoupled Learning: Mitigating Gradient Staleness in
  Inter-Layer Model Parallelization
Accumulated Decoupled Learning: Mitigating Gradient Staleness in Inter-Layer Model Parallelization
Huiping Zhuang
Zhiping Lin
Kar-Ann Toh
124
4
0
03 Dec 2020
On-Chip Error-triggered Learning of Multi-layer Memristive Spiking
  Neural Networks
On-Chip Error-triggered Learning of Multi-layer Memristive Spiking Neural Networks
Melika Payvand
M. Fouda
Fadi J. Kurdahi
A. Eltawil
Emre Neftci
61
30
0
21 Nov 2020
Self Normalizing Flows
Self Normalizing Flows
Thomas Anderson Keller
Jorn W. T. Peters
P. Jaini
Emiel Hoogeboom
Patrick Forré
Max Welling
74
14
0
14 Nov 2020
Fast & Slow Learning: Incorporating Synthetic Gradients in Neural Memory
  Controllers
Fast & Slow Learning: Incorporating Synthetic Gradients in Neural Memory Controllers
Tharindu Fernando
Simon Denman
Sridha Sridharan
Clinton Fookes
88
0
0
10 Nov 2020
From Eye-blinks to State Construction: Diagnostic Benchmarks for Online
  Representation Learning
From Eye-blinks to State Construction: Diagnostic Benchmarks for Online Representation Learning
Banafsheh Rafiee
Zaheer Abbas
Sina Ghiassian
Raksha Kumaraswamy
R. Sutton
Elliot A. Ludvig
Adam White
OffRL
59
17
0
09 Nov 2020
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