286 citations
- Fujitsu (Japan)JP5 papers
- Eindhoven University of TechnologyNL4 papers
- Fujitsu (China)CN4 papers
- Stanford UniversityUS4 papers
- Argonne National LaboratoryUS3 papers
- Carnegie Mellon UniversityUS3 papers
- University of DelawareUS3 papers
- University of Southern CaliforniaUS3 papers
- California Institute of TechnologyUS2 papers
- Clemson UniversityUS2 papers
- Columbia UniversityUS2 papers
- Cornell UniversityUS2 papers
39 papers
ASAP: Visual Analytics for Identifying and Analyzing Image Patterns in AI-generated Images
Jinbin Huang, Yuki Ueno, Chen Chen +4
Generative image models can produce highly realistic images, raising concerns about potential misuse in creating deceptive content. Current deepfake approaches face several challen…
Neural-Parameterized Cellular Automata for Wildfire Spread
Maksym Zhenirovskyy, Ion Matei, Rohit Vuppala +2
Traditional wildfire models rely on rigid, low-dimensional parameters and static fuel maps, frequently underpredicting fire spread. To address this weakness, we introduce a hybrid…
A Modular Approach to Succinct Arguments for QMA
James Bartusek, Jiahui Liu, Giulio Malavolta
Succinct argument systems are of central importance to modern crytpography, enabling the efficient verification of computational claims. In the classical setting, Kilian (STOC 92)…
User Perceptions vs. Proxy LLM Judges: Privacy and Helpfulness in LLM Responses to Privacy-Sensitive Scenarios
Xiaoyuan Wu, Roshni Kaushik, Wenkai Li +2
Large language models (LLMs) are rapidly being adopted for tasks like drafting emails, summarizing meetings, and answering health questions. In these settings, users may need to sh…
The Lie Algebra of XY-mixer Topologies and Warm Starting QAOA for Constrained Optimization
Steven Kordonowy, Hannes Leipold
The XY-mixer has widespread utilization in modern quantum computing, including in variational quantum algorithms, such as Quantum Alternating Operator Ansatz (QAOA). The XY ansatz…
Contextual Quantum Neural Networks for Stock Price Prediction
Sharan Mourya, Hannes Leipold, Bibhas Adhikari
In this paper, we apply quantum machine learning (QML) to predict the stock prices of multiple assets using a contextual quantum neural network. Our approach captures recent trends…