Comparing performance of different InfoNCE type losses used in contrastive learning.
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Updated
Jun 12, 2024 - Python
Comparing performance of different InfoNCE type losses used in contrastive learning.
Implementation for <Learning with Hyperspherical Uniformity> in AISTATS'21.
Implementation of uniformity tests on the circle and (hyper)sphere, with a C++ core. The package allows the replication of the data application in "On a projection-based class of uniformity tests on the hypersphere"
Multiobjective Discrete Optimization Framework in Julia
Tools for maintaining a unified SimplePie development environment.
JumpBackHash: Say Goodbye to the Modulo Operation to Distribute Keys Uniformly to Buckets
User Scenarios through User Interaction Diagrams (US-UIDs) is a format to Automated Acceptance Tests.
Compares four different methods for generating uniformly distributed random points within a unit circle
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