The two-dimensional sphere embedded in three-dimensional Euclidean space S2, plays a central role in a variety of scientific and engineering domains, including geophysics, planetary science, geodesy, atmospheric physics, quantum chemistry, cosmology, and virtual reality, among many others. As machine learning increasin...
Thorsten Kurth, M. Rietmann, M. Bisson et al.· 0 citations
As deep learning for physical systems continues to grow in popularity, efforts to improve generalizability have primarily focused on designing architectures that embed physical constraints. However, for machine-learning surrogate climate models (emulators), we show that the low structural diversity in existing scenario...
Christopher B. Womack, Shahine Bouabid, Andrei Sokolov et al.· 0 citations
Cloud robotics is an innovative field that leverages cloud technologies-including cloud computing (CC), cloud storage, deep learning, big data, and the Internet of Things to augment the capabilities of robotics. This integration facilitates the execution of robotic functions through a converged infrastructure and share...
Shahnawaz Ahmad, Shahadat Hussain, Khalid Anwar et al.· International Conference on...· 2 citations
Interstellar communication is not merely slow. It is strategically stale. A message received across distance reports a sender that may no longer occupy the same strategic state, while replies and irreversible actions are chosen on different local clocks. This paper develops a delayed Bayesian interaction game in which...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
Interstellar communication is not merely slow. It is strategically stale. A message received across distance reports a sender that may no longer occupy the same strategic state, while replies and irreversible actions are chosen on different local clocks. This paper develops a delayed Bayesian interaction game in which...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
Interstellar game models normally allow strategies to change while holding fixed the players, technologies, preferences, feasible actions and payoff structure. This assumption is least credible for advanced civilisations operating across long technological and evolutionary horizons. This paper develops an Endogenous Ga...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
Interstellar game models normally allow strategies to change while holding fixed the players, technologies, preferences, feasible actions and payoff structure. This assumption is least credible for advanced civilisations operating across long technological and evolutionary horizons. This paper develops an Endogenous Ga...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
Interstellar game models normally allow strategies to change while holding fixed the players, technologies, preferences, feasible actions and payoff structure. This assumption is least credible for advanced civilisations operating across long technological and evolutionary horizons. This paper develops an Endogenous Ga...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
Interstellar game models normally allow strategies to change while holding fixed the players, technologies, preferences, feasible actions and payoff structure. This assumption is least credible for advanced civilisations operating across long technological and evolutionary horizons. This paper develops an Endogenous Ga...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
Dark Forest arguments commonly reduce interstellar strategy to a bilateral encounter between two persistent civilisations. A galaxy, however, is an open population in which civilisations enter, disappear, form selective relationships and occupy a spatially constrained network. This paper develops a continuous-time Gala...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.