most citedOptimizing Ansatz Design in QAOA for Max-cut

20 citations · 21 across the 5 of their papers we have counts for

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5 papers

quant-ph20211 cited

Efficient Decoding of Surface Code Syndromes for Error Correction in Quantum Computing

Debasmita Bhoumik, Pinaki Sen, Ritajit Majumdar +3

Errors in surface code have typically been decoded by Minimum Weight Perfect Matching (MWPM) based method. Recently, neural-network-based Machine Learning (ML) techniques have been…

quant-ph2021

Depth Optimized Ansatz Circuit in QAOA for Max-Cut

Ritajit Majumdar, Debasmita Bhoumik, Dhiraj Madan +3

While a Quantum Approximate Optimization Algorithm (QAOA) is intended to provide a quantum advantage in finding approximate solutions to combinatorial optimization problems, noise…

quant-ph202120 cited

Optimizing Ansatz Design in QAOA for Max-cut

Ritajit Majumdar, Dhiraj Madan, Debasmita Bhoumik +3

Quantum Approximate Optimization Algorithm (QAOA) is studied primarily to find approximate solutions to combinatorial optimization problems. For a graph with vertices and e…

cs.LG2020

A machine learning based heuristic to predict the efficacy of online sale

Aditya Vikram Singhania, Saronyo Lal Mukherjee, Ritajit Majumdar +3

It is difficult to decide upon the efficacy of an online sale simply from the discount offered on commodities. Different features have different influence on the price of a product…

cs.LG2020

An Empirical Study of Incremental Learning in Neural Network with Noisy Training Set

Shovik Ganguly, Atrayee Chatterjee, Debasmita Bhoumik +1

The notion of incremental learning is to train an ANN algorithm in stages, as and when newer training data arrives. Incremental learning is becoming widespread in recent times with…