33 citations · 73 across the 11 of their papers we have counts for
11 papers
Verifiable Random Sampling
Yeoh Wei Zhu, Soorya Rethinasamy, Anthony Alexiades Armenakas +3
Verifiable random functions (VRF) underpin a wide range of applications that require publicly verifiable evaluations of a pseudorandom function on a given input. However, once the…
A Practical Post-Quantum Distributed Ledger Protocol for Financial Institutions
Yeoh Wei Zhu, Naresh Goud Boddu, Yao Ma +5
Traditional financial institutions face inefficiencies that can be addressed by distributed ledger technology. However, a primary barrier to adoption is the privacy concerns surrou…
A Numerical Gradient Inversion Attack in Variational Quantum Neural-Networks
Georgios Papadopoulos, Shaltiel Eloul, Yash Satsangi +4
The loss landscape of Variational Quantum Neural Networks (VQNNs) is characterized by local minima that grow exponentially with increasing qubits. Because of this, it is more chall…
Certified randomness using a trapped-ion quantum processor
Minzhao Liu, Ruslan Shaydulin, Pradeep Niroula +29
While quantum computers have the potential to perform a wide range of practically important tasks beyond the capabilities of classical computers, realizing this potential remains a…
Applications of Certified Randomness
Omar Amer, Shouvanik Chakrabarti, Kaushik Chakraborty +8
Certified randomness can be generated with untrusted remote quantum computers using multiple known protocols, one of which has been recently realized experimentally. Unlike the ran…
Private, Auditable, and Distributed Ledger for Financial Institutes
Shaltiel Eloul, Yash Satsangi, Yeoh Wei Zhu +3
Distributed ledger technology offers several advantages for banking and finance industry, including efficient transaction processing and cross-party transaction reconciliation. The…
Expressive variational quantum circuits provide inherent privacy in federated learning
Niraj Kumar, Jamie Heredge, Changhao Li +3
Federated learning has emerged as a viable distributed solution to train machine learning models without the actual need to share data with the central aggregator. However, standar…
Topical: Learning Repository Embeddings from Source Code using Attention
Agathe Lherondelle, Varun Babbar, Yash Satsangi +3
This paper presents Topical, a novel deep neural network for repository level embeddings. Existing methods, reliant on natural language documentation or naive aggregation technique…
Enhancing Privacy against Inversion Attacks in Federated Learning by using Mixing Gradients Strategies
Shaltiel Eloul, Fran Silavong, Sanket Kamthe +2
Federated learning reduces the risk of information leakage, but remains vulnerable to attacks. We investigate how several neural network design decisions can defend against gradien…
Nano-Pump base on Exothermic Surface Reactions
Shaltiel Eloul, Daan Frenkel
We present simulations indicating that it should be possible to construct a switchable nano-scale fluid pump, driven by exothermic surface reactions. Such a pump could, for instanc…
'Rocket propulsion' of Janus micro-swimmers
Shaltiel Eloul, Wilson C K Poon, Oded Farago +1
We report simulations of a spherical Janus particle undergoing exothermic surface reactions around one pole only. Our model excludes self-phoretic transport by design. Nevertheless…