Get our free extension to see links to code for papers anywhere online!

Chrome logo  Add to Chrome

Firefox logo Add to Firefox
Picture for Seth Lloyd

Seth Lloyd
Alert button

Joint Embedding Self-Supervised Learning in the Kernel Regime


Sep 29, 2022
Bobak T. Kiani, Randall Balestriero, Yubei Chen, Seth Lloyd, Yann LeCun

Add code
Alert button

Figure 1 for Joint Embedding Self-Supervised Learning in the Kernel Regime
Figure 2 for Joint Embedding Self-Supervised Learning in the Kernel Regime
Figure 3 for Joint Embedding Self-Supervised Learning in the Kernel Regime
Figure 4 for Joint Embedding Self-Supervised Learning in the Kernel Regime

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

projUNN: efficient method for training deep networks with unitary matrices


Mar 11, 2022
Bobak Kiani, Randall Balestriero, Yann Lecun, Seth Lloyd

Add code
Alert button

Figure 1 for projUNN: efficient method for training deep networks with unitary matrices
Figure 2 for projUNN: efficient method for training deep networks with unitary matrices
Figure 3 for projUNN: efficient method for training deep networks with unitary matrices
Figure 4 for projUNN: efficient method for training deep networks with unitary matrices

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Quantum algorithms for group convolution, cross-correlation, and equivariant transformations


Sep 23, 2021
Grecia Castelazo, Quynh T. Nguyen, Giacomo De Palma, Dirk Englund, Seth Lloyd, Bobak T. Kiani

Add code
Alert button

Figure 1 for Quantum algorithms for group convolution, cross-correlation, and equivariant transformations
Figure 2 for Quantum algorithms for group convolution, cross-correlation, and equivariant transformations
Figure 3 for Quantum algorithms for group convolution, cross-correlation, and equivariant transformations
Figure 4 for Quantum algorithms for group convolution, cross-correlation, and equivariant transformations

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

A quantum algorithm for training wide and deep classical neural networks


Jul 19, 2021
Alexander Zlokapa, Hartmut Neven, Seth Lloyd

Add code
Alert button

Figure 1 for A quantum algorithm for training wide and deep classical neural networks
Figure 2 for A quantum algorithm for training wide and deep classical neural networks
Figure 3 for A quantum algorithm for training wide and deep classical neural networks
Figure 4 for A quantum algorithm for training wide and deep classical neural networks
* 10 pages + 13 page appendix, 10 figures; code available at https://github.com/quantummind/quantum-deep-neural-network 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Quantum Earth Mover's Distance: A New Approach to Learning Quantum Data


Jan 08, 2021
Bobak Toussi Kiani, Giacomo De Palma, Milad Marvian, Zi-Wen Liu, Seth Lloyd

Add code
Alert button

Figure 1 for Quantum Earth Mover's Distance: A New Approach to Learning Quantum Data
Figure 2 for Quantum Earth Mover's Distance: A New Approach to Learning Quantum Data
Figure 3 for Quantum Earth Mover's Distance: A New Approach to Learning Quantum Data
Figure 4 for Quantum Earth Mover's Distance: A New Approach to Learning Quantum Data

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Adversarial robustness guarantees for random deep neural networks


Apr 13, 2020
Giacomo De Palma, Bobak T. Kiani, Seth Lloyd

Add code
Alert button

Figure 1 for Adversarial robustness guarantees for random deep neural networks
Figure 2 for Adversarial robustness guarantees for random deep neural networks
Figure 3 for Adversarial robustness guarantees for random deep neural networks
Figure 4 for Adversarial robustness guarantees for random deep neural networks

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Learning Unitaries by Gradient Descent


Feb 18, 2020
Bobak Toussi Kiani, Seth Lloyd, Reevu Maity

Add code
Alert button

Figure 1 for Learning Unitaries by Gradient Descent
Figure 2 for Learning Unitaries by Gradient Descent
Figure 3 for Learning Unitaries by Gradient Descent
Figure 4 for Learning Unitaries by Gradient Descent

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email
1
2
>>