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Rajiv Krishnakumar

@rajivkrishnakumar.bsky.social

I like quantum algorithms ⚛ Any/all 🚹 Quantum scientist @ QuantumBasel and QC2, Univeristät Basel 🇮🇳🇨🇭 Opinions are my own

84 Posts131 Follower65 Folgt
Rajiv Krishnakumar@rajivkrishnakumar.bsky.social · 3mo ago

Test analogy on NISQ vs Fault-Tolerant (FT). NISQ is easy to get started on but unclear ultimate potential - like path that is initially easy but the top is clouded. FT has a clear(er) path, but tougher to start and still some known and unknown challenges before it's useful. Feedback/thoughts?

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Rajiv Krishnakumar@rajivkrishnakumar.bsky.social · 6mo ago

Paper on taking the classical surrogate of QML models! ieeexplore.ieee.org/abstract/doc... Taking a classical surrogate means we took a hybrid QML model and translated the quantum layer to a "classical surrogate" so that the whole model can be run efficiently on a classical computer.

Experimental Validation of Dequantization of Hybrid Quantum Machine Learning Models Using Classical Surrogates

Dequantization of quantum machine learning models is the methodology of creating an equivalent classical model using a partial Fourier series over the classical input variables such that the classical...

ieeexplore.ieee.org

Rajiv Krishnakumar@rajivkrishnakumar.bsky.social · 8mo ago

Very excited that the book 𝗤𝘂𝗮𝗻𝘁𝘂𝗺 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝗶𝗲𝘀: 𝗧𝗿𝗲𝗻𝗱𝘀 𝗮𝗻𝗱 𝗜𝗺𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝗖𝘆𝗯𝗲𝗿 𝗗𝗲𝗳𝗲𝗻𝘀𝗲 is finally out, which includes my chapter on 𝗤𝘂𝗮𝗻𝘁𝘂𝗺 𝗧𝗵𝗿𝗲𝗮𝘁𝘀: link.springer.com/chapter/10.1...

Quantum Threats

With the recent advancements in quantum computing, there is a threat that today’s widely used digital encryption schemes will become vulnerable to cryptography-breaking quantum algorithms. In pa...

link.springer.com

Rajiv Krishnakumar@rajivkrishnakumar.bsky.social · last yr.

Glad to see our work on potential applications of quantum computing to biomarker discovery out in the @cellpress.bsky.social Patterns journal :) www.cell.com/patterns/ful...

How quantum computing can enhance biomarker discovery

The authors discuss how quantum computing can improve biomarker discovery. This perspective highlights the application of quantum algorithms in analyzing complex healthcare data, including electronic ...

cell.com

Rajiv Krishnakumar@rajivkrishnakumar.bsky.social · 2y ago

📜 New preprint on Potential Applications of Quantum Computing to Healthcare and Lifesciences 🧬 ⚛️

arxiv.org/abs/2411.10511

In this preprint we discuss some challenges in biomarker discovery and how we think quantum computing could potentially help. We look at various use-cases across 3... (1/4)

Rajiv Krishnakumar@rajivkrishnakumar.bsky.social · last yr.

(1/8) New Preprint: Advancing AI for Detecting Circulating Rare Cells (CRCs) – A Collaboration Between Moonlight AI & QuantumBasel arxiv.org/abs/2503.10510 📜 In this paper, we demonstrate an improvement of existing attention-based deep multiple instance learning (MIL) AI methods

Extreme Learning Machines for Attention-based Multiple Instance Learning in Whole-Slide Image Classification

Whole-slide image classification represents a key challenge in computational pathology and medicine. Attention-based multiple instance learning (MIL) has emerged as an effective approach for this prob...

arxiv.org

Quanta Magazine@quantamagazine.org · 2y ago

The second law of thermodynamics states that a quantity called entropy is on the rise, indicating that the universe is predisposed to disorder. But the idea of entropy is evolving. www.quantamagazine.org/what-is-entr...

What Is Entropy? A Measure of Just How Little We Really Know. | Quanta Magazine

Exactly 200 years ago, a French engineer introduced an idea that would quantify the universe’s inexorable slide into decay. But entropy, as it’s currently understood, is less a fact about the world th...

quantamagazine.org