Search Results
Fractal AI: A fragile theory of intelligence
Fractal AI is a theory for general artificial intelligence.
Accelerating Inverse Learning via Intelligent Localization with Exploratory Sampling
In the scope of "AI for Science", solving inverse problems is a longstanding challenge in materials and drug discovery, where the goal is to determine the hidden structures given a set of desirable properties.
AnalogGenie: A Generative Engine for Automatic Discovery of Analog Circuit Topologies
Yet, applying generative AI techniques to accelerate the design of analog ICs remains a significant challenge due to critical domain-specific issues, such as the lack of a comprehensive dataset and effective representation methods for analog circuits.
GenSC-6G: A Prototype Testbed for Integrated Generative AI, Quantum, and Semantic Communication
We introduce a prototyping testbed, GenSC-6G, developed to generate a comprehensive dataset that supports the integration of generative artificial intelligence (AI), quantum computing, and semantic communication for emerging sixth-generation (6G) applications.
Explaining Quantum Circuits with Shapley Values: Towards Explainable Quantum Machine Learning
Quantum gates constitute the building blocks of gate-based quantum hardware and form circuits that can be used for quantum computations.
Explainable Artificial Intelligence (XAI)
Quantum Machine Learning
Virtual Reality for Understanding Artificial-Intelligence-driven Scientific Discovery with an Application in Quantum Optics
Thereby, we can manually discover new generalizations of AI-discoveries as well as new understanding in experimental quantum optics.
A Quantum Natural Language Processing Approach to Musical Intelligence
In particular, we are importing methods from the Distributional Compositional Categorical (DisCoCat) modelling framework for Natural Language Processing (NLP), motivated by musical grammars.
NCoder -- A Quantum Field Theory approach to encoding data
In this paper we present a novel approach to interpretable AI inspired by Quantum Field Theory (QFT) which we call the NCoder.
AI-Assisted Rapid Crystal Structure Generation Towards a Target Local Environment
In the field of material design, traditional crystal structure prediction approaches require extensive structural sampling through computationally expensive energy minimization methods using either force fields or quantum mechanical simulations.
