2

Seasonal Arctic sea ice forecasting with probabilistic deep learning
Cite
Tighter Risk Certificates for Neural Networks
Cite
High-Dimensional Bayesian Optimization with Manifold Gaussian Processes
Bayesian optimization (BO) is a powerful approach for seeking the global optimum of expensive black-box functions and has proven …
PDF Cite Code
A Foliated View of Transfer Learning
Transfer learning considers a learning process where a new task is solved by transferring relevant knowledge from known solutions to …
PDF Cite
Estimating Barycenters of Measures in High Dimensions
Barycentric averaging is a principled way of summarizing populations of measures. Existing algorithms for estimating barycenters …
PDF Cite
Aligning Time Series on Incomparable Spaces
Dynamic time warping (DTW) is a useful method for aligning, comparing and combining time series, but it requires them to live in …
PDF Cite Code
Aligning Time Series on Incomparable Spaces
High-Dimensional Bayesian Optimization with Projections using Quantile Gaussian Processes
Key challenges of Bayesian optimization in high dimensions are both learning the response surface and optimizing an acquisition …
PDF Cite DOI
A PAC-Bayesian perspective on structured prediction with implicit loss embeddings
Cite
Consolidated Dataset and Metrics for High-Dynamic-Range Image Quality
Cite
Spatio-chromatic contrast sensitivity under mesopic and photopic light levels
Cite