The Rectified Gaussian Distribution

A simple but powerful modification of the standard Gaussian dis(cid: 173) tribution is studied. The variables of the rectified Gaussian are constrained to be nonnegative, enabling the use of nonconvex en(cid: 173) ergy functions. Two multimodal examples, the competitive and cooperative distributions, illustrate the representational power of the rectified Gaussian. Since the cooperative distribution can rep(cid: 173) resent the translations of a pattern, it demonstrates the potential of the rectified Gaussian for modeling pattern manifolds.

Authors

• Nicholas Socci
• Daniel Lee Adobe
• H. Sebastian Seung Princeton University

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