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projUNN: efficient method for training deep networks with unitary
  matrices

projUNN: efficient method for training deep networks with unitary matrices

10 March 2022
B. Kiani
Randall Balestriero
Yann LeCun
S. Lloyd
ArXivPDFHTML

Papers citing "projUNN: efficient method for training deep networks with unitary matrices"

28 / 28 papers shown
Title
HadamRNN: Binary and Sparse Ternary Orthogonal RNNs
HadamRNN: Binary and Sparse Ternary Orthogonal RNNs
Armand Foucault
Franck Mamalet
François Malgouyres
MQ
85
0
0
28 Jan 2025
Unitary convolutions for learning on graphs and groups
Unitary convolutions for learning on graphs and groups
B. Kiani
Lukas Fesser
Melanie Weber
GNN
45
1
0
07 Oct 2024
Training-efficient density quantum machine learning
Training-efficient density quantum machine learning
Brian Coyle
El Amine Cherrat
Nishant Jain
Natansh Mathur
Snehal Raj
Skander Kazdaghli
Iordanis Kerenidis
47
5
0
30 May 2024
Input-driven circuit reconfiguration in critical recurrent neural
  networks.Marcelo O. Magnasco
Input-driven circuit reconfiguration in critical recurrent neural networks.Marcelo O. Magnasco
M. Magnasco
26
1
0
23 May 2024
Neural Controlled Differential Equations with Quantum Hidden Evolutions
Neural Controlled Differential Equations with Quantum Hidden Evolutions
Lingyi Yang
Zhen Shao
29
0
0
30 Apr 2024
Graph Unitary Message Passing
Graph Unitary Message Passing
Haiquan Qiu
Yatao Bian
Quanming Yao
37
2
0
17 Mar 2024
Backward Lens: Projecting Language Model Gradients into the Vocabulary
  Space
Backward Lens: Projecting Language Model Gradients into the Vocabulary Space
Shahar Katz
Yonatan Belinkov
Mor Geva
Lior Wolf
63
10
1
20 Feb 2024
Generating Universal Adversarial Perturbations for Quantum Classifiers
Generating Universal Adversarial Perturbations for Quantum Classifiers
Gautham Anil
Vishnu Vinod
Apurva Narayan
AAML
19
4
0
13 Feb 2024
Quantized Approximately Orthogonal Recurrent Neural Networks
Quantized Approximately Orthogonal Recurrent Neural Networks
Armand Foucault
Franck Mamalet
Franccois Malgouyres
MQ
34
1
0
05 Feb 2024
Coloring Deep CNN Layers with Activation Hue Loss
Coloring Deep CNN Layers with Activation Hue Loss
Louis-Franccois Bouchard
Mohsen Ben Lazreg
Matthew Toews
LLMSV
33
0
0
05 Oct 2023
Self-Supervised Learning with Lie Symmetries for Partial Differential
  Equations
Self-Supervised Learning with Lie Symmetries for Partial Differential Equations
Grégoire Mialon
Q. Garrido
Hannah Lawrence
Danyal Rehman
Yann LeCun
B. Kiani
SSL
32
26
0
11 Jul 2023
Stabilized Neural Differential Equations for Learning Dynamics with
  Explicit Constraints
Stabilized Neural Differential Equations for Learning Dynamics with Explicit Constraints
Alistair J R White
Niki Kilbertus
Maximilian Gelbrecht
Niklas Boers
20
6
0
16 Jun 2023
Efficient Storage of Fine-Tuned Models via Low-Rank Approximation of
  Weight Residuals
Efficient Storage of Fine-Tuned Models via Low-Rank Approximation of Weight Residuals
Simo Ryu
S. Seo
Jaejun Yoo
37
5
0
28 May 2023
Edit at your own risk: evaluating the robustness of edited models to
  distribution shifts
Edit at your own risk: evaluating the robustness of edited models to distribution shifts
Davis Brown
Charles Godfrey
Cody Nizinski
Jonathan Tu
Henry Kvinge
KELM
29
8
0
28 Feb 2023
Rock Guitar Tablature Generation via Natural Language Processing
Rock Guitar Tablature Generation via Natural Language Processing
Josue Casco-Rodriguez
37
1
0
12 Jan 2023
DOSnet as a Non-Black-Box PDE Solver: When Deep Learning Meets Operator
  Splitting
DOSnet as a Non-Black-Box PDE Solver: When Deep Learning Meets Operator Splitting
Yuan Lan
Zerui Li
Jie Sun
Yang Xiang
18
10
0
11 Dec 2022
Improved techniques for deterministic l2 robustness
Improved techniques for deterministic l2 robustness
Sahil Singla
S. Feizi
AAML
23
9
0
15 Nov 2022
Testing predictions of representation cost theory with CNNs
Testing predictions of representation cost theory with CNNs
Charles Godfrey
Elise Bishoff
Myles Mckay
Davis Brown
Grayson Jorgenson
Henry Kvinge
E. Byler
24
0
0
03 Oct 2022
Quantum Vision Transformers
Quantum Vision Transformers
El Amine Cherrat
Iordanis Kerenidis
Natansh Mathur
Jonas Landman
M. Strahm
Yun. Y Li
ViT
39
55
0
16 Sep 2022
Assessing the Unitary RNN as an End-to-End Compositional Model of Syntax
Assessing the Unitary RNN as an End-to-End Compositional Model of Syntax
Jean-Philippe Bernardy
Shalom Lappin
49
1
0
11 Aug 2022
U(1) Symmetry-breaking Observed in Generic CNN Bottleneck Layers
U(1) Symmetry-breaking Observed in Generic CNN Bottleneck Layers
Louis-Franccois Bouchard
Mohsen Ben Lazreg
Matthew Toews
31
0
0
05 Jun 2022
Path Development Network with Finite-dimensional Lie Group
  Representation
Path Development Network with Finite-dimensional Lie Group Representation
Han Lou
Siran Li
Hao Ni
18
7
0
02 Apr 2022
On the Minimal Adversarial Perturbation for Deep Neural Networks with
  Provable Estimation Error
On the Minimal Adversarial Perturbation for Deep Neural Networks with Provable Estimation Error
Fabio Brau
Giulio Rossolini
Alessandro Biondi
Giorgio Buttazzo
AAML
29
7
0
04 Jan 2022
Implicit Bias of Linear Equivariant Networks
Implicit Bias of Linear Equivariant Networks
Hannah Lawrence
Kristian Georgiev
A. Dienes
B. Kiani
AI4CE
40
14
0
12 Oct 2021
Quantum algorithms for group convolution, cross-correlation, and
  equivariant transformations
Quantum algorithms for group convolution, cross-correlation, and equivariant transformations
Grecia Castelazo
Quynh T. Nguyen
Giacomo De Palma
Dirk Englund
S. Lloyd
B. Kiani
45
11
0
23 Sep 2021
Existence, Stability and Scalability of Orthogonal Convolutional Neural
  Networks
Existence, Stability and Scalability of Orthogonal Convolutional Neural Networks
El Mehdi Achour
Franccois Malgouyres
Franck Mamalet
16
20
0
12 Aug 2021
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train
  10,000-Layer Vanilla Convolutional Neural Networks
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks
Lechao Xiao
Yasaman Bahri
Jascha Narain Sohl-Dickstein
S. Schoenholz
Jeffrey Pennington
244
349
0
14 Jun 2018
Learning Unitary Operators with Help From u(n)
Learning Unitary Operators with Help From u(n)
Stephanie L. Hyland
Gunnar Rätsch
97
41
0
17 Jul 2016
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