FSML Lecture Series – Panos Stinis: When big neural networks are not enough: physics, multi-fidelity and kernels
2004 Lay Auto LabWhen big neural networks are not enough: physics, multi-fidelity and kernels
10 events found.
Events
FSML
Events
FSML Lecture Series – Ricardo Vinuesa: Identifying coherent structures and controlling turbulent flows through deep learning
2210 Lurie Engineering Center 1221 Beal Ave, Ann Arbor, MIIdentifying coherent structures and controlling turbulent flows through deep learning
FSML Lecture Series – Doruk Aksoy: From Turbulent Flows to Video Games: Managing Large-Scale Data with Tensor Decomposition
2636 GGBA 2350 Hayward St, Ann Arbor, MI, United StatesFrom Turbulent Flows to Video Games: Managing Large-Scale Data with Tensor Decomposition
FSML Lecture Series – Alexander Tong (Mila – Quebec AI Institute): Flow matching in cell trajectories and protein design
1642 GGBL 2350 HAYWARD ST, Ann Arbor, United StatesFlow matching in cell trajectories and protein design
FSML Lecture Series – Lianghao Cao (Caltech): Derivative-Informed Operator Learning with Applications to Cost-Efficient Bayesian Inversion
2636 GGBA 2350 Hayward St, Ann Arbor, MI, United StatesFlow matching in cell trajectories and protein design
FSML Lecture Series – Julie Bessac (National Renewable Energy Laboratory): Statistical learning for Summary Statistics of Physics-based Model Outputs and their Correction and Probabilistic Outputs from Neural Networks applied to Super-resolution
GG Brown Laboratory - 2636Statistical learning for Summary Statistics of Physics-based Model Outputs and their Correction and Probabilistic Outputs from Neural Networks applied to Super-resolution
FSML Lecture Series – Smita Krishnaswamy (Yale University): Dynamics Models of Cellular and Neuronal Interactions
GG Brown Laboratory - 1642Dynamics Models of Cellular and Neuronal Interactions
Frontiers in Scientific Machine Learning Seminar – Ashwin Renganathan (Penn State): Sample-efficient and Principled Decision-making with Expensive Stochastic Oracles
GG Brown Laboratory - 1642Sample-efficient and Principled Decision-making with Expensive Stochastic Oracles
Frontiers in Scientific Machine Learning Seminar – Pan Du (University of Notre Dame): Conditional neural field latent diffusion model for generating spatiotemporal turbulence
GG Brown Laboratory - 1642Conditional neural field latent diffusion model for generating spatiotemporal turbulence
Frontiers in Scientific Machine Learning Seminar – Romit Maulik (Penn State University): SALSA-RL: Stability Analysis in the Latent Space of Actions for Reinforcement Learning
2004 Lay Auto LabConditional neural field latent diffusion model for generating spatiotemporal turbulence