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Found 7 papers, 0 papers with code
Accelerated Design and Deployment of Low-Carbon Concrete for Data Centers
Finally, we report on how these formulations were used in the construction of buildings and structures in a Meta data center in DeKalb, IL, USA.
Learning from One and Only One Shot
Using simply the nearest-neighbor classifier on this similarity space, we achieve human-level character recognition using only 1--10 examples per class and nothing else (no pre-training).
Information Lattice Learning
ILL focuses on explainability and generalizability from "small data", and aims for rules akin to those humans distill from experience (rather than a representation optimized for a specific task like classification).
Human Evaluation of Interpretability: The Case of AI-Generated Music Knowledge
Interpretability of machine learning models has gained more and more attention among researchers in the artificial intelligence (AI) and human-computer interaction (HCI) communities.
A Group-Theoretic Approach to Computational Abstraction: Symmetry-Driven Hierarchical Clustering
Abstraction plays a key role in concept learning and knowledge discovery; this paper is concerned with computational abstraction.
Probabilistic Rule Realization and Selection
Abstraction and realization are bilateral processes that are key in deriving intelligence and creativity.
Learning Interpretable Musical Compositional Rules and Traces
Throughout music history, theorists have identified and documented interpretable rules that capture the decisions of composers.
