Publication

Applications of Approximate Learning and Inference for Probabilistic Models

Related publications (213)

About
Privacy
Disclaimer

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Applications of Approximate Learning and Inference for Probabilistic Models

Graph Chatbot

Chat with Graph Search

Bed Topography Inference from Velocity Field Using Deep Learning.

Breaking the Curse of Dimensionality in Deep Neural Networks by Learning Invariant Representations

Deep Learning Generalization with Limited and Noisy Labels

Robust Outlier Rejection for 3D Registration with Variational Bayes

Automatic Parameterization for Aerodynamic Shape Optimization via Deep Geometric Learning

Backpropagation-free training of deep physical neural networks

The inductive bias of deep learning: Connecting weights and functions

Semi-Supervised Deep Learning Representations in Earth Observation Based Forest Management

Robust discrete choice models with t-distributed kernel errors

Machine Learning Methods for Robust Uncertainty Quantification and Controller Approximation