Supanut Thanasilp

16 papers Journal 16

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	IQP Born Machines under Data-dependent and Agnostic Initialization Strategies. CoRR Sacha Lerch, Joseph Bowles, Ricard Puig, Erik Armengol, Zoë Holmes, Supanut Thanasilp
2025	J	`jnl`	A unifying account of warm start guarantees for patches of quantum landscapes. CoRR Hela Mhiri, Ricard Puig-i-Valls, Sacha Lerch, Manuel S. Rudolph, Thiparat Chotibut, Supanut Thanasilp, Zoë Holmes
2025	J	`jnl`	Connecting phases of matter to the flatness of the loss landscape in analog variational quantum algorithms. CoRR Kasidit Srimahajariyapong, Supanut Thanasilp, Thiparat Chotibut
2025	J	`jnl`	On fundamental aspects of quantum extreme learning machines. Quantum Mach. Intell. Weijie Xiong, Giorgio Facelli, Mehrad Sahebi, Owen Agnel, Thiparat Chotibut, Supanut Thanasilp, Zoë Holmes
2025	J	`jnl`	Role of scrambling and noise in temporal information processing with quantum systems. CoRR Weijie Xiong, Zoë Holmes, Armando Angrisani, Yudai Suzuki, Thiparat Chotibut, Supanut Thanasilp
2024	J	`jnl`	A Review of Barren Plateaus in Variational Quantum Computing. CoRR Martin Larocca, Supanut Thanasilp, Samson Wang, Kunal Sharma, Jacob D. Biamonte, Patrick J. Coles, Lukasz Cincio, Jarrod R. McClean, Zoë Holmes, Marco Cerezo
2024	J	`jnl`	Efficient quantum-enhanced classical simulation for patches of quantum landscapes. CoRR Sacha Lerch, Ricard Puig-i-Valls, Manuel S. Rudolph, Armando Angrisani, Tyson Jones, Marco Cerezo, Supanut Thanasilp, Zoë Holmes
2024	J	`jnl`	Variational quantum simulation: a case study for understanding warm starts. CoRR Ricard Puig-i-Valls, Marc Drudis, Supanut Thanasilp, Zoë Holmes
2023	J	`jnl`	A Unified Framework for Trace-induced Quantum Kernels. CoRR Beng Yee Gan, Daniel Leykam, Supanut Thanasilp
2023	J	`jnl`	Does provable absence of barren plateaus imply classical simulability? Or, why we need to rethink variational quantum computing. CoRR 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
2023	J	`jnl`	On fundamental aspects of quantum extreme learning machines. CoRR Weijie Xiong, Giorgio Facelli, Mehrad Sahebi, Owen Agnel, Thiparat Chotibut, Supanut Thanasilp, Zoë Holmes
2023	J	`jnl`	Subtleties in the trainability of quantum machine learning models. Quantum Mach. Intell. Supanut Thanasilp, Samson Wang, Nhat A. Nghiem, Patrick J. Coles, Marco Cerezo
2023	J	`jnl`	Trainability barriers and opportunities in quantum generative modeling. CoRR Manuel S. Rudolph, Sacha Lerch, Supanut Thanasilp, Oriel Kiss, Sofia Vallecorsa, Michele Grossi, Zoë Holmes
2022	J	`jnl`	Exponential concentration and untrainability in quantum kernel methods. CoRR Supanut Thanasilp, Samson Wang, Marco Cerezo, Zoë Holmes
2021	J	`jnl`	Qubit-efficient encoding schemes for binary optimisation problems. Quantum Benjamin Tan, Marc-Antoine Lemonde, Supanut Thanasilp, Jirawat Tangpanitanon, Dimitris G. Angelakis
2021	J	`jnl`	Subtleties in the trainability of quantum machine learning models. CoRR Supanut Thanasilp, Samson Wang, Nhat A. Nghiem, Patrick J. Coles, Marco Cerezo