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Do you have a dataset you think could benefit from quantum learning?

Keep reading!

7 months ago 0 1 1 0

Late to post, but still worth a read: our conceptual paper on a quantum mulitomics platform: arxiv.org/pdf/2506.14080

7 months ago 1 1 0 0

On Wednesday I'm giving a talk at the Quantum Mechanics for Modeling Classical Dynamics symposium at the Society for Industrial and Applied Mathematics Conference on Dynamical Systems (DS25) in Denver. Looking forward to the discussions and let's connect if you're around and interested in the topic!

11 months ago 1 1 0 0

I really enjoyed this wide-ranging discussion about quantum physics and the possibilities of using it in computing with Amit Prakash and Dheeraj Pandey! Perfect timing for it to be released on World Quantum Day yesterday :)

youtube.com/watch?v=ysPY...

1 year ago 1 1 0 0
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A Practical Framework for Assessing the Performance of Observable Estimation in Quantum Simulation Simulating dynamics of physical systems is a key application of quantum computing, with potential impact in fields such as condensed matter physics and quantum chemistry. However, current quantum algo...

We are proud to have contributed to the latest enhancements to the open-source QED-C Application-Oriented Benchmark suite. Check out this new paper on benchmarking algorithmic techniques for the computation of observables in Hamiltonian simulation.

arxiv.org/abs/2504.09813

1 year ago 0 1 0 0
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Very gratifying to present today at the APS meeting in Anaheim California

1 year ago 1 1 1 0
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Quantum Machine Learning: Theory and Training 11:30 am – 2:30 pm, Friday March 21, Session MAR-X34, Anaheim Convention Center, 256A (Level 2)

Two talks with contributions from Coherent Computing at the APS Global Physics Summit this week:

- Techniques for design and training of large quantum machine learning models, presented by me
summit.aps.org/events/MAR-X...

1 year ago 3 2 1 0
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Bit-bit encoding, optimizer-free training and sub-net initialization: techniques for scalable quantum machine learning Quantum machine learning for classical data is currently perceived to have a scalability problem due to (i) a bottleneck at the point of loading data into quantum states, (ii) the lack of clarity arou...

First publication of 2025 is up on arxiv!

arxiv.org/abs/2501.02148

1 year ago 3 2 0 0
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