activity
20132024
most citedPS1-10jh: The Disruption of a Main-Sequence Star of Near-Solar Composition

315 citations · 479 across the 8 of their papers we have counts for

collaborators

10 papers

quant-ph2024

Quantum control in artificial neurons with superconductor-ionic memory inserted in the feedback

Osama M. Nayfeh, Haik Manukian, Matthew Kelly +1

To improve artificial intelligence/autonomous systems and help with treating neurological conditions, there's a requirement for artificial neuron hardware that mimics biological. W…

cs.LG2021

Mode-Assisted Joint Training of Deep Boltzmann Machines

Haik Manukian, Massimiliano Di Ventra

The deep extension of the restricted Boltzmann machine (RBM), known as the deep Boltzmann machine (DBM), is an expressive family of machine learning models which can serve as compa…

cs.LG2020★ 32 cited

Mode-Assisted Unsupervised Learning of Restricted Boltzmann Machines

Haik Manukian, Yan Ru Pei, Sean R. B. Bearden +1

Restricted Boltzmann machines (RBMs) are a powerful class of generative models, but their training requires computing a gradient that, unlike supervised backpropagation on typical…

cs.LG2019★ 3 cited

Data Generation for Neural Programming by Example

Judith Clymo, Haik Manukian, Nathanaël Fijalkow +2

Programming by example is the problem of synthesizing a program from a small set of input / output pairs. Recent works applying machine learning methods to this task show promise,…

cs.LG2019★ 18 cited

Generating Weighted MAX-2-SAT Instances of Tunable Difficulty with Frustrated Loops

Yan Ru Pei, Haik Manukian, Massimiliano Di Ventra

Many optimization problems can be cast into the maximum satisfiability (MAX-SAT) form, and many solvers have been developed for tackling such problems. To evaluate a MAX-SAT solver…

cs.LG2018

Accelerating Deep Learning with Memcomputing

Haik Manukian, Fabio L. Traversa, Massimiliano Di Ventra

Restricted Boltzmann machines (RBMs) and their extensions, called 'deep-belief networks', are powerful neural networks that have found applications in the fields of machine learnin…

cs.ET2017★ 33 cited

Instantons in self-organizing logic gates

Sean R. B. Bearden, Haik Manukian, Fabio L. Traversa +1

Self-organizing logic is a recently-suggested framework that allows the solution of Boolean truth tables "in reverse," i.e., it is able to satisfy the logical proposition of gates…

cs.ET2016★ 11 cited

Memcomputing Numerical Inversion with Self-Organizing Logic Gates

Haik Manukian, Fabio L. Traversa, Massimiliano Di Ventra

We propose to use Digital Memcomputing Machines (DMMs), implemented with self-organizing logic gates (SOLGs), to solve the problem of numerical inversion. Starting from fixed-point…

astro-ph.HE2013★ 67 cited

Turbovelocity Stars: Kicks Resulting From the Tidal Disruption of Solitary Stars

Haik Manukian, James Guillochon, Enrico Ramirez-Ruiz +1

The centers of most known galaxies host supermassive black holes (SMBHs). In orbit around these black holes are a centrally-concentrated distribution of stars, both in single and i…

astro-ph.HE2013★ 315 cited

PS1-10jh: The Disruption of a Main-Sequence Star of Near-Solar Composition

James Guillochon, Haik Manukian, Enrico Ramirez-Ruiz

When a star comes within a critical distance to a supermassive black hole (SMBH), immense tidal forces disrupt the star, resulting in a stream of debris that falls back onto the SM…