2 citations · 3 across the 7 of their papers we have counts for
9 papers
From Quantum Tunneling to Classical Optimization through Instantons
Jiayu Shen, Dylan Herman, Guneykan Ozgul +5
We use an instanton-based analysis to show that Path Integral Stochastic Gradient Descent (PISGD), a classical optimization algorithm instantiated from path integral Monte Carlo (P…
CRUMB: Efficient Prior Fitted Network Inference via Distributionally Matched Context Batching
Jamie Heredge, Mattia J. Villani, Pranav Deshpande +2
Prior-fitted networks (PFNs) are a promising class of tabular foundation models that perform in-context learning, whereby the entire labelled training set is supplied as context, a…
Entropy Distribution as a Fingerprint for Hallucinations in Generative Models
Mattia J. Villani, Pranav Deshpande, Akshay Seshadri +2
Large Language Models (LLMs) often generate factually incorrect outputs, commonly termed hallucinations, that undermine trust and limit deployment in high-stakes settings. Existing…
An efficient method for spot-checking quantum properties with sequential trials
Yanbao Zhang, Akshay Seshadri, Emanuel Knill
In practical situations, the reliability of quantum resources can be compromised due to complex generation processes or adversarial manipulations during transmission. Consequently,…
Digital signatures with classical shadows on near-term quantum computers
Pradeep Niroula, Minzhao Liu, Sivaprasad Omanakuttan +15
Quantum mechanics provides cryptographic primitives whose security is grounded in hardness assumptions independent of those underlying classical cryptography. However, existing pro…
A Unified Framework for Provably Efficient Algorithms to Estimate Shapley Values
Tyler Chen, Akshay Seshadri, Mattia J. Villani +7
Shapley values have emerged as a critical tool for explaining which features impact the decisions made by machine learning models. However, computing exact Shapley values is diffic…
Provably faster randomized and quantum algorithms for -means clustering via uniform sampling
Tyler Chen, Archan Ray, Akshay Seshadri +6
The -means algorithm (Lloyd's algorithm) is a widely used method for clustering unlabeled data. A key bottleneck of the -means algorithm is that each iteration requires time…
Adaptive and Robust Watermark for Generative Tabular Data
Dung Daniel Ngo, Archan Ray, Akshay Seshadri +6
In recent years, watermarking generative tabular data has become a prominent framework to protect against the misuse of synthetic data. However, while most prior work in watermarki…
Local measurement strategies for multipartite entanglement quantification
Luke Coffman, Akshay Seshadri, Graeme Smith +1
Despite multipartite entanglement being a global property of a quantum state, a number of recent works have made it clear that it can be quantified using only local measurements. T…