Joseph Bowles
@josephbowles.bsky.social
Quantum machine learning @ Xanadu
Reposted by Joseph Bowles
5️⃣/🔟 In Scientific Reports, 5 of the top 10 most cited articles have an article number of 1.
5️⃣/🔟 In Nature Communications the same: 5 of the top 10 are article 1s.
Coincidence? 👇
scirate.com/arxiv/2511.0...
I think not.
5️⃣/🔟 In Nature Communications the same: 5 of the top 10 are article 1s.
Coincidence? 👇
scirate.com/arxiv/2511.0...
I think not.
November 4, 2025 at 3:59 PM
5️⃣/🔟 In Scientific Reports, 5 of the top 10 most cited articles have an article number of 1.
5️⃣/🔟 In Nature Communications the same: 5 of the top 10 are article 1s.
Coincidence? 👇
scirate.com/arxiv/2511.0...
I think not.
5️⃣/🔟 In Nature Communications the same: 5 of the top 10 are article 1s.
Coincidence? 👇
scirate.com/arxiv/2511.0...
I think not.
Very excited to release our latest paper on generative QML. Much to our own surprise, we show that it is feasible to train quantum models with up to a thousand qubits and hundreds of thousands of parameters, all on classical hardware.
scirate.com/arxiv/2503.0...
scirate.com/arxiv/2503.0...
Train on classical, deploy on quantum: scaling generative quantum machine learning to a thousand qubits
We propose an approach to generative quantum machine learning that overcomes the fundamental scaling issues of variational quantum circuits. The core idea is to use a class of generative models based ...
scirate.com
March 6, 2025 at 10:33 AM
Very excited to release our latest paper on generative QML. Much to our own surprise, we show that it is feasible to train quantum models with up to a thousand qubits and hundreds of thousands of parameters, all on classical hardware.
scirate.com/arxiv/2503.0...
scirate.com/arxiv/2503.0...
We recently released a software package to optimize IQP circuits that scales to millions of qubits and gates. Our main motivation was quantum machine learning (paper on the way!), but we believe there could be many other applications.
arxiv.org/abs/2501.04776
github.com/XanaduAI/iqp...
arxiv.org/abs/2501.04776
github.com/XanaduAI/iqp...
IQPopt: Fast optimization of instantaneous quantum polynomial circuits in JAX
IQPopt is a software package designed to optimize large-scale instantaneous quantum polynomial circuits on classical hardware. By exploiting an efficient classical simulation algorithm for expectation...
arxiv.org
January 20, 2025 at 9:45 AM
We recently released a software package to optimize IQP circuits that scales to millions of qubits and gates. Our main motivation was quantum machine learning (paper on the way!), but we believe there could be many other applications.
arxiv.org/abs/2501.04776
github.com/XanaduAI/iqp...
arxiv.org/abs/2501.04776
github.com/XanaduAI/iqp...