124 citations · 134 across the 16 of their papers we have counts for
17 papers
Unifying and Extending Strong Simulation of Quantum Circuits
Floris Geerts, Rihan Hai, Matthias Lanzinger +3
We establish functional aggregate queries (FAQs) as a unifying language for exact classical simulation of quantum circuits. A circuit becomes a sum-product query: factors encode ga…
QuWARP: A Workload-Aware Reuse Planner for simulating Quantum Circuits
Tim Littau, Rihan Hai
Quantum circuit simulation often appears as repeated-run workloads rather than isolated circuits: variational quantum eigensolver (VQE) sweeps, noisy multishot studies, and quantum…
InferQ: A Database-Oriented Benchmark for Quantum Circuits Simulation
Andrei Ilinescu, Aadi Patwardhan, Rihan Hai
Recent work suggests that relational database management systems (RDBMSs) can execute quantum circuit simulation by compiling the simulation into SQL workloads (primarily join-and-…
Quadratic Sums-of-Powers for Fixed-Parameter Tractable Quantum-Circuit Simulation
Alexis de Colnet, Floris Geerts, Rihan Hai +3
Strongly simulating a quantum circuit, that is, computing an output amplitude, can be done by summing the circuit's Feynman paths: a weighted count over assignments to Boolean path…
Harpoon: Generalised Manifold Guidance for Conditional Tabular Diffusion
Aditya Shankar, Yuandou Wang, Rihan Hai +1
Generating tabular data under conditions is critical to applications requiring precise control over the generative process. Existing methods rely on training-time strategies that d…
Parity Cross-Resonance: A Multiqubit Gate
Xuexin Xu, Siyu Wang, Radhika Joshi +2
We present a native three-qubit entangling gate that exploits engineered interactions to realize control-control-target and control-target-target operations in a single coherent st…
CEBench: A Benchmarking Toolkit for the Cost-Effectiveness of LLM Pipelines
Wenbo Sun, Jiaqi Wang, Qiming Guo +3
Online Large Language Model (LLM) services such as ChatGPT and Claude 3 have transformed business operations and academic research by effortlessly enabling new opportunities. Howev…
Share Secrets for Privacy: Confidential Forecasting with Vertical Federated Learning
Aditya Shankar, Jérémie Decouchant, Dimitra Gkorou +2
Vertical federated learning (VFL) is a promising area for time series forecasting in many applications, such as healthcare and manufacturing. Critical challenges to address include…
Model Selection with Model Zoo via Graph Learning
Ziyu Li, Hilco van der Wilk, Danning Zhan +3
Pre-trained deep learning (DL) models are increasingly accessible in public repositories, i.e., model zoos. Given a new prediction task, finding the best model to fine-tune can be…
SiloFuse: Cross-silo Synthetic Data Generation with Latent Tabular Diffusion Models
Aditya Shankar, Hans Brouwer, Rihan Hai +1
Synthetic tabular data is crucial for sharing and augmenting data across silos, especially for enterprises with proprietary data. However, existing synthesizers are designed for ce…
Quantum Data Management: From Theory to Opportunities
Rihan Hai, Shih-Han Hung, Sebastian Feld
Quantum computing has emerged as a transformative tool for future data management. Classical problems in database domains, including query optimization, data integration, and trans…
Accelerating Machine Learning Queries with Linear Algebra Query Processing
Wenbo Sun, Asterios Katsifodimos, Rihan Hai
The rapid growth of large-scale machine learning (ML) models has led numerous commercial companies to utilize ML models for generating predictive results to help business decision-…
Metadata Representations for Queryable ML Model Zoos
Ziyu Li, Rihan Hai, Alessandro Bozzon +1
Machine learning (ML) practitioners and organizations are building model zoos of pre-trained models, containing metadata describing properties of the ML models and datasets that ar…
SiMa: Effective and Efficient Matching Across Data Silos Using Graph Neural Networks
Christos Koutras, Rihan Hai, Kyriakos Psarakis +2
How can we leverage existing column relationships within silos, to predict similar ones across silos? Can we do this efficiently and effectively? Existing matching approaches do no…
Amalur: Data Integration Meets Machine Learning
Rihan Hai, Christos Koutras, Andra Ionescu +5
The data needed for machine learning (ML) model training, can reside in different separate sites often termed data silos. For data-intensive ML applications, data silos pose a majo…
Data Lakes: A Survey of Functions and Systems
Rihan Hai, Christos Koutras, Christoph Quix +1
Data lakes are becoming increasingly prevalent for big data management and data analytics. In contrast to traditional 'schema-on-write' approaches such as data warehouses, data lak…
Theoretical study of the stripline ferromagnetic resonance response of metallic ferromagnetic films based on an analytical model
Rihan Hai, Mikhail Kostylev
We develop an advanced analytical model for calculating the broadband stripline ferromagnetic resonance (FMR) response for metallic ferromagnetic films, taking into account the exc…