Supanut Thanasilp

According to our database, Supanut Thanasilp authored at least 14 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

IQP Born Machines under Data-dependent and Agnostic Initialization Strategies.

Sacha Lerch, Joseph Bowles, Ricard Puig, Erik Armengol, Zoë Holmes, Supanut Thanasilp

CoRR, March, 2026

2025

On fundamental aspects of quantum extreme learning machines.

Weijie Xiong, Giorgio Facelli, Mehrad Sahebi, Owen Agnel, Thiparat Chotibut, Supanut Thanasilp, Zoë Holmes

Quantum Mach. Intell., June, 2025

Connecting phases of matter to the flatness of the loss landscape in analog variational quantum algorithms.

Kasidit Srimahajariyapong, Supanut Thanasilp, Thiparat Chotibut

CoRR, June, 2025

Role of scrambling and noise in temporal information processing with quantum systems.

Weijie Xiong, Zoë Holmes, Armando Angrisani, Yudai Suzuki, Thiparat Chotibut, Supanut Thanasilp

CoRR, May, 2025

A unifying account of warm start guarantees for patches of quantum landscapes.

Hela Mhiri, Ricard Puig-i-Valls, Sacha Lerch, Manuel S. Rudolph, Thiparat Chotibut, Supanut Thanasilp, Zoë Holmes

CoRR, February, 2025

2024

Efficient quantum-enhanced classical simulation for patches of quantum landscapes.

Sacha Lerch, Ricard Puig-i-Valls, Manuel S. Rudolph, Armando Angrisani, Tyson Jones, Marco Cerezo, Supanut Thanasilp, Zoë Holmes

CoRR, 2024

A Review of Barren Plateaus in Variational Quantum Computing.

Martin Larocca, Supanut Thanasilp, Samson Wang, Kunal Sharma, Jacob D. Biamonte, Patrick J. Coles, Lukasz Cincio, Jarrod R. McClean, Zoë Holmes, Marco Cerezo

CoRR, 2024

Variational quantum simulation: a case study for understanding warm starts.

Ricard Puig-i-Valls, Marc Drudis, Supanut Thanasilp, Zoë Holmes

CoRR, 2024

2023

Subtleties in the trainability of quantum machine learning models.

Supanut Thanasilp, Samson Wang, Nhat A. Nghiem, Patrick J. Coles, Marco Cerezo

Quantum Mach. Intell., June, 2023

Does provable absence of barren plateaus imply classical simulability? Or, why we need to rethink variational quantum computing.

Marco Cerezo, Martin Larocca, Diego García-Martín, Nelson L. Diaz, Paolo Braccia, Enrico Fontana, Manuel S. Rudolph, Pablo Bermejo, Aroosa Ijaz, Supanut Thanasilp, Eric R. Anschuetz, Zoë Holmes

CoRR, 2023

A Unified Framework for Trace-induced Quantum Kernels.

Beng Yee Gan, Daniel Leykam, Supanut Thanasilp

CoRR, 2023

Trainability barriers and opportunities in quantum generative modeling.

Manuel S. Rudolph, Sacha Lerch, Supanut Thanasilp, Oriel Kiss, Sofia Vallecorsa, Michele Grossi, Zoë Holmes

CoRR, 2023

2022

Exponential concentration and untrainability in quantum kernel methods.

Supanut Thanasilp, Samson Wang, Marco Cerezo, Zoë Holmes

CoRR, 2022

2021

Qubit-efficient encoding schemes for binary optimisation problems.

Benjamin Tan, Marc-Antoine Lemonde, Supanut Thanasilp, Jirawat Tangpanitanon, Dimitris G. Angelakis

Quantum, 2021