46 citations · 74 across the 7 of their papers we have counts for
13 papers
Computing on Functions Using Randomized Vector Representations
E. Paxon Frady, Denis Kleyko, Christopher J. Kymn +2
Vector space models for symbolic processing that encode symbols by random vectors have been proposed in cognitive science and connectionist communities under the names Vector Symbo…
Disentangling images with Lie group transformations and sparse coding
Ho Yin Chau, Frank Qiu, Yubei Chen +1
Discrete spatial patterns and their continuous transformations are two important regularities contained in natural signals. Lie groups and representation theory are mathematical to…
Resonator networks for factoring distributed representations of data structures
E. Paxon Frady, Spencer Kent, Bruno A. Olshausen +1
The ability to encode and manipulate data structures with distributed neural representations could qualitatively enhance the capabilities of traditional neural networks by supporti…
Tent: Fully Test-time Adaptation by Entropy Minimization
Dequan Wang, Evan Shelhamer, Shaoteng Liu +2
A model must adapt itself to generalize to new and different data during testing. In this setting of fully test-time adaptation the model has only the test data and its own paramet…
Word Embedding Visualization Via Dictionary Learning
Juexiao Zhang, Yubei Chen, Brian Cheung +1
Co-occurrence statistics based word embedding techniques have proved to be very useful in extracting the semantic and syntactic representation of words as low dimensional continuou…
Dynamic Scale Inference by Entropy Minimization
Dequan Wang, Evan Shelhamer, Bruno Olshausen +1
Given the variety of the visual world there is not one true scale for recognition: objects may appear at drastically different sizes across the visual field. Rather than enumerate…