Ngā tūemi rite

• Multi-fidelity Gaussian process surrogate modeling for regression problems in physics
  mā: Ravi, Kislaya, me ētahi atu.
  I whakaputaina: (2024)
• Learning from the past: predicting critical transitions with machine learning trained on surrogates of historical data
  mā: Ma, Zhiqin, me ētahi atu.
  I whakaputaina: (2024)
• Learning thermodynamically constrained equations of state with uncertainty
  mā: Sharma, Himanshu, me ētahi atu.
  I whakaputaina: (2023)
• Physics-constrained polynomial chaos expansion for scientific machine learning and uncertainty quantification
  mā: Sharma, Himanshu, me ētahi atu.
  I whakaputaina: (2024)
• GeoConformal prediction: a model-agnostic framework of measuring the uncertainty of spatial prediction
  mā: Lou, Xiayin, me ētahi atu.
  I whakaputaina: (2024)