IBM Quantum的动态

Quantum Machine Learning’—a new learning course— is now available for partners in the IBM Quantum Network. https://ibm.co/3ChDcri One of the most promising applications for quantum computing is data with complex structures. This new course introduces three of the most well-studied approaches—variational quantum circuits, VQCs with parallels to quantum neural networks, and quantum kernel estimation. This learning opportunity will provide a brief overview of related classical machine learning paradigms and explains how quantum computing plays a role. The course also shows learners how to integrate quantum computing results into existing classical workflows. For example, one use case within the lesson shows how to use a precomputed kernel matrix estimated using a quantum computer in a classical classifier in sklearn. The course is now available on the IBM Quantum Learning platform linked above, and once users complete the course, they can take an exam to earn a quantum machine learning badge via Credly.

Quantum Computing: A powerful tool for potentially enhancing machine learning

>- Not my work - sharing resources -< Great paper today: "Single-shot quantum machine learning" by Erik Recio Armengol, Jens Eisert, and Johannes Jakob Meyer Abstract: Quantum machine learning aims to improve learning methods through the use of quantum computers. If it is to ever realize its potential, many obstacles need to be overcome. A particularly pressing one arises at the prediction stage because the outputs of quantum learning models are inherently random. This creates an often considerable overhead, as many executions of a quantum learning model have to be aggregated to obtain an actual prediction. In this work, we analyze when quantum learning models can evade this issue and produce predictions in a near-deterministic way – paving the way to single-shot quantum machine learning. We give a rigorous definition of single-shotness in quantum classifiers and show that the degree to which a quantum learning model is near-deterministic is constrained by the distinguishability of the embedded quantum states used in the model. Opening the black box of the embedding, we show that if the embedding is realized by quantum circuits, a certain depth is necessary for single-shotness to be even possible. We conclude by showing that quantum learning models cannot be single-shot in a generic way and trainable at the same time. Link: https://lnkd.in/eyKE439p #quantummachinelearning #quantumcomputing #research #researchpaper

Quantum Kernels Unlock New Possibilities in Machine Learning by Quantum News via Quantum Zeitgeist, Quantum Computing and QML ([Global] Quantum Computing) URL: https://ift.tt/X89iPoJ The quest for large-scale, fault-tolerant quantum computing has been intense in recent years, but researchers have already reported achieving quantum advantage for impractical problems. To take it a step further, there is growing interest in achieving quantum advantage for practical problems. One of the most promising candidates for this goal is quantum machine learning (QML). In this article, we explore the rise of QML and its potential to unlock new possibilities in machine learning. https://ift.tt/8F0y95Y

Can you use AI in Quantum Computing? Here’s the blog which provides an introduction to Quantum ML. Code is available on my Github repo : https://lnkd.in/d8RdCpqG https://lnkd.in/dn-DbUkN

A Quick Introduction to Quantum Machine Learning for Non-Practitioners.

Quantum Computing India Cohort 4 #Quantum30 challenge Day 26: Quantum Classification from QML --------------------------------------------------------------------------------- ?? QML is a captivating field that marries the power of quantum computing with the artistry of machine learning. Imagine a symphony where qubits dance to the rhythm of data, creating harmonious patterns that classical computers can only dream of. ?? ?? The Quantum Playground In the vast quantum playground, algorithms pirouette gracefully, revealing patterns in data that defy classical intuition. These quantum systems, with their counter-intuitive behaviors, beckon us to explore their potential. ?? ?? What Is Quantum Machine Learning? At its core, QML seeks to harness quantum phenomena to enhance machine learning tasks. It’s like giving our algorithms a pair of quantum wings—allowing them to soar beyond classical limitations. ?? ?? Three Acts of Quantum Learning - Supervised Learning: Imagine a quantum tutor guiding our algorithms through a cosmic maze. With quantum-enhanced classifiers, we decipher encrypted messages, predict stock market trends, and even unravel the mysteries of protein folding. ?? - Unsupervised Learning: Here, our quantum apprentice explores uncharted territories. Clusters emerge from quantum fog, revealing hidden patterns in data. Think of it as a celestial treasure hunt! ??? - Reinforcement Learning: Quantum agents play games with the universe itself. They learn by interacting with their environment, adapting and evolving. It’s like teaching a star to dance! ?? ?? Challenges and Enchantments - Hardware Quest: Quantum computers are delicate instruments, akin to Stradivarius violins. We seek the perfect notes—error-corrected qubits, fault-tolerant gates—to compose our quantum symphony. - Software Sonata: Crafting quantum software is an art. We weave quantum circuits, entanglements, and quantum neural networks. Our code whispers to the quantum realm. - Adversarial Sorcery: Beware! Quantum classifiers are vulnerable to adversarial spells. Their high-dimensional Hilbert spaces can be tampered with. But fear not; we wield quantum shields! ?? ?? Read more about Quantum Machine Learning: https://lnkd.in/dwwzZnzz https://lnkd.in/dq82MAMW ?????? #Quantum #MachineLearning #QuantumComputing #LinkedIn

Quantum computing, coupled with generative AI, is on the cusp of revolutionising technology. In this interesting article, researchers explore how machine learning models can generate quantum circuits based on textual prompts describing specific quantum operations. Question is: Is your organisation seizing this moment to extend your Data Analytics platform with ML/AI capabilities to support the rapidly evolving ML use cases? ??

"A recent study by researchers from CSIRO and the University of Melbourne has made progress in quantum machine learning, a field aimed at achieving quantum advantage to outperform classical machine learning. Their work demonstrates that?quantum circuits?for data encoding in quantum machine learning can be greatly simplified without compromising accuracy or robustness. The research was?published?Sept. 12 in?Intelligent Computing. The team's results, validated through both simulations and experiments on IBM quantum devices, show that their innovative encoding methods reduced circuit depth by a factor of 100 on average compared to traditional approaches while achieving similar classification accuracies. The findings offer an exciting new pathway for the practical application of quantum machine learning on current quantum devices." #ai #ml #quantumencoding #circuitcomplexity #machinelearning

? Day 27 Of #Quantum30 challenge: Today's topic was Quantum Machine Learning (QML) using Amazon Braket Key takeaways: -> Today I explored QML in Amazon Braket Hybrid Jobs which comprised of training a parameterized quantum circuit for an unsupervised generative modelling task. -> Generative modelling is a form of unsupervised learning aimed at creating new synthetic samples that mimic an unknown target probability distribution and quantum circuits are well-suited for generative modelling due to their intrinsic probabilistic nature. -> Amazon Braket Hybrid Jobs allow users to seamlessly combine classical and quantum processing within a single workflow which facilitates the execution of both classical and quantum tasks, enabling the integration of classical optimization algorithms with quantum computations. -> By leveraging the strengths of both classical and quantum computing, Amazon Braket Hybrid Jobs enable more efficient and effective solutions to complex computational problems. #QuantumComputingIndia #quantumcomputing #quantumtechnology