Quantum Machine Learning

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CellStrat > Research/Blog > Artificial Intelligence > Quantum Machine Learning
06
Sep
Overview of Quantum Machine Learning

Author : Niraj Kale Submitted on : 5 Sep 2020 Abstract – Machine learning has come a long way since the perceptron was introduced in the 1950s. With more advanced ML algorithms there is a need for speed to achieve higher accuracy. Quantum computation can help in achieving higher calculations per second which can exponentially […]

Posted in: papers, Quantum Machine Learning,
06
Feb
NLP Embeddings with GLoVe, RL Policy Gradients, Quantum Neural Networks

#CellStratAILab #disrupt4.0 #WeCreateAISuperstars Last Saturday (1st Feb 2020), our AI Lab researchers delivered superb presentations on advanced topics. First Shreyas S K started with detailed algorithmic discussion with GLoVe and T-SNE algos. Then he showed how these can be used for Sarcasm Detection in news articles. Detection of sarcasm is of great importance and beneficial […]

Posted in: Natural Language Processing, Quantum Computing, Quantum Machine Learning, Reinforcement Learning,
Tags: GLoVe, policy gradients, qGAN, quantum neural network, reinforcement learning, sarcasm detection, t-sne, TFIDF, word embedding,
09
Jan
1
Quantum Machine Learning; Practical Object Detector

#CellStratAILab #disrupt4.0 #WeCreateAISuperstars CellStrat is India’s No 1 open AI Lab with more than 120 AI researchers and interns engaged in advanced AI skilling and research. The first AI Lab meetup in this New Year 2020 saw amazing demos and presentations by our AI Lab members. Quantum Machine Learning (Quantum Computing) :- First Niraj Kale […]

Posted in: Computer Vision, Deep Learning, Quantum Computing, Quantum Machine Learning,
Tags: Bernstein–Vazirani, boch sphere, Constrained Scheduling, constraint satisfaction problem, data augmentation, data collection, Dwave, entanglement, Fast RCNN, Faster RCNN, feature extractor, googlenet, image classification, image processing, IOU, mAP, Mobilenet, object detection, p-bit, qGANs, QisKit QSVM, quantum annealing, quantum computing, Quantum counting, quantum data, quantum gates, quantum machine learning, quantum neural network, Quantum phase estimation algorithm, quantum tunnelling, RCNN, Region proposals, Shor's algorithm, single shot detector, superposition, tensorflow,