{"id":"arxiv:2502.15104","title":"Estimating Neural Representation Alignment from Sparsely Sampled Inputs and Features","date":"2025-02-20","section":"Representation alignment","quality":0.498999,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bb284056f9389cbe75ad82bc3d85b997ce69212d23f95de2baf599ad64d97618/","source_url":"https://arxiv.org/abs/2502.15104","text_available":true,"authors":["Chanwoo Chun","Abdulkadir Canatar","SueYeon Chung","Daniel D. 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Neural Representation Alignment from Sparsely Sampled Inputs and Features","offset":0,"level":1,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bb284056f9389cbe75ad82bc3d85b997ce69212d23f95de2baf599ad64d97618/part-1.html#text"},{"title":"Abstract","offset":88,"level":2,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bb284056f9389cbe75ad82bc3d85b997ce69212d23f95de2baf599ad64d97618/part-1.html#text"},{"title":"Introduction","offset":1589,"level":2,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bb284056f9389cbe75ad82bc3d85b997ce69212d23f95de2baf599ad64d97618/part-1.html#text"},{"title":"Problem Statement","offset":5094,"level":2,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bb284056f9389cbe75ad82bc3d85b997ce69212d23f95de2baf599ad64d97618/part-1.html#text"},{"title":"Our Contribution","offset":7466,"level":2,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bb284056f9389cbe75ad82bc3d85b997ce69212d23f95de2baf599ad64d97618/part-1.html#text"},{"title":"Definitions","offset":8250,"level":2,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bb284056f9389cbe75ad82bc3d85b997ce69212d23f95de2baf599ad64d97618/part-1.html#text"},{"title":"Centered Kernel Alignment","offset":8266,"level":3,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bb284056f9389cbe75ad82bc3d85b997ce69212d23f95de2baf599ad64d97618/part-1.html#text"},{"title":"Measurement matrix","offset":10431,"level":3,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bb284056f9389cbe75ad82bc3d85b997ce69212d23f95de2baf599ad64d97618/part-1.html#text"},{"title":"Existing CKA estimators","offset":11879,"level":2,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bb284056f9389cbe75ad82bc3d85b997ce69212d23f95de2baf599ad64d97618/part-1.html#text"},{"title":"Naive Estimator","offset":12082,"level":3,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bb284056f9389cbe75ad82bc3d85b997ce69212d23f95de2baf599ad64d97618/part-1.html#text"},{"title":"Stimulus-Corrected Estimator","offset":13324,"level":3,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bb284056f9389cbe75ad82bc3d85b997ce69212d23f95de2baf599ad64d97618/part-1.html#text"},{"title":"Bias of the Existing Estimator","offset":15622,"level":3,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bb284056f9389cbe75ad82bc3d85b997ce69212d23f95de2baf599ad64d97618/part-1.html#text"},{"title":"Stimulus-Neuron-Corrected 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estimators","offset":35535,"level":2,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bb284056f9389cbe75ad82bc3d85b997ce69212d23f95de2baf599ad64d97618/part-3.html#text"},{"title":"A.1 Expression of ℋ \\mathcal{H} in terms of the uncentered kernel","offset":35598,"level":3,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bb284056f9389cbe75ad82bc3d85b997ce69212d23f95de2baf599ad64d97618/part-3.html#text"},{"title":"A.2 Identifying the source of bias in the naive estimator","offset":37498,"level":3,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bb284056f9389cbe75ad82bc3d85b997ce69212d23f95de2baf599ad64d97618/part-3.html#text"},{"title":"A.3 Derivation of the stimulus-corrected ℋ \\mathcal{H} estimator","offset":41651,"level":3,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bb284056f9389cbe75ad82bc3d85b997ce69212d23f95de2baf599ad64d97618/part-3.html#text"},{"title":"A.4 Derivation of the stimulus-neuron-corrected ℋ \\mathcal{H} estimator","offset":46715,"level":3,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bb284056f9389cbe75ad82bc3d85b997ce69212d23f95de2baf599ad64d97618/part-3.html#text"},{"title":"Appendix B Bias analysis","offset":49379,"level":2,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bb284056f9389cbe75ad82bc3d85b997ce69212d23f95de2baf599ad64d97618/part-4.html#text"},{"title":"B.1 Generative process framework","offset":49408,"level":3,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bb284056f9389cbe75ad82bc3d85b997ce69212d23f95de2baf599ad64d97618/part-4.html#text"},{"title":"B.2 Biases in CKA estimators contributed by the biases in HSIC estimators","offset":52728,"level":3,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/bb284056f9389cbe75ad82bc3d85b997ce69212d23f95de2baf599ad64d97618/part-4.html#text"},{"title":"B.3 Analyzing the overall ℋ ^ \\widehat{\\mathcal{H}} 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