Researcher

Bernhard Schölkopf

Profile

Bernhard Schölkopf is one of the architects of kernel methods in machine learning, co-developing support vector machines and kernel principal component analysis. More recently, his lab has become the foremost academic group pursuing causality-aware machine learning, arguing that current neural networks lack causal understanding and will fail in distribution shift. Schölkopf received the ACM Prize in Computing in 2023 and the Leibniz Prize from the German Research Foundation.

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