171 citations · 307 across the 8 of their papers we have counts for
8 papers
Role of energetic ions in the growth of fcc and ω crystalline phases in Ti films deposited by HiPIMS
David Dellasega, Francesco Mirani, Davide Vavassori +2
Titanium (Ti), due to its excellent properties, is widely exploited in thin film technology that usually leads to the production of α-phase (hcp) Ti films. In this work, we investi…
Bio-Inspired Hashing for Unsupervised Similarity Search
Chaitanya K. Ryali, John J. Hopfield, Leopold Grinberg +1
The fruit fly Drosophila's olfactory circuit has inspired a new locality sensitive hashing (LSH) algorithm, FlyHash. In contrast with classical LSH algorithms that produce low dime…
Local Unsupervised Learning for Image Analysis
Leopold Grinberg, John Hopfield, Dmitry Krotov
Local Hebbian learning is believed to be inferior in performance to end-to-end training using a backpropagation algorithm. We question this popular belief by designing a local algo…
Unsupervised Learning by Competing Hidden Units
Dmitry Krotov, John Hopfield
It is widely believed that the backpropagation algorithm is essential for learning good feature detectors in early layers of artificial neural networks, so that these detectors are…
Dense Associative Memory is Robust to Adversarial Inputs
Dmitry Krotov, John J Hopfield
Deep neural networks (DNN) trained in a supervised way suffer from two known problems. First, the minima of the objective function used in learning correspond to data points (also…
Dense Associative Memory for Pattern Recognition
Dmitry Krotov, John J Hopfield
A model of associative memory is studied, which stores and reliably retrieves many more patterns than the number of neurons in the network. We propose a simple duality between this…
Sequence reproduction, single trial learning, and mimicry based on a mammalian-like distributed code for time
J. J. Hopfield, Carlos D. Brody
Animals learn tasks requiring a sequence of actions over time. Waiting a given time before taking an action is a simple example. Mimicry is a complex example, e.g. in humans, hummi…
Searching for memories, Sudoku, implicit check-bits, and the iterative use of not-always-correct rapid neural computation
J. J. Hopfield
The algorithms that simple feedback neural circuits representing a brain area can rapidly carry out are often adequate to solve only easy problems, and for more difficult problems…