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Ila Fiete
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Ila Fiete10 visible / 10 total nodes / 16 links

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Co-authorshipCo-authorshipCo-authorshipAuthorshipWorks onAuthorshipWorks onWorks onAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipTopic signalTopic signalAuthorshipIla FieteAIla FieteResearcherAttractor Geometry of Transformer Memory: From Conflict Arbitration to Confident HallucinationWAttractor Geometry of T...preprint / 2026Qiyao LiangAQiyao LiangResearcherRisto MiikkulainenARisto MiikkulainenResearcherA binary Hopfield network with $1/\log(n)$ information rate and applications to grid cell decodingWA binary Hopfield netwo...preprint / 2014Artificial IntelligenceTArtificial Intelligence22915 worksHow to Train Your Wide Neural Network Without Backprop: An Input-Weight Alignment PerspectiveWHow to Train Your Wide ...preprint / 2022Superlinear Precision and Memory in Simple Population CodesWSuperlinear Precision a...preprint / 2020Training recurrent networks to generate hypotheses about how the brain solves hard navigation problemsWTraining recurrent netw...preprint / 2016Map Induction: Compositional spatial submap learning for efficient exploration in novel environmentsWMap Induction: Composit...preprint / 2022
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Ila Fiete

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PaperAttractor Geometry of Transformer Memory: From Conflict Arbitration to Confident HallucinationAuthorship / preprint / 2026PersonQiyao LiangCo-authorship / ResearcherPersonRisto MiikkulainenCo-authorship / ResearcherPaperA binary Hopfield network with 1/log⁡(n)1/\log(n) information rate and applications to grid cell decodingAuthorship / preprint / 2014TopicArtificial IntelligenceWorks on / 22915 worksPaperHow to Train Your Wide Neural Network Without Backprop: An Input-Weight Alignment PerspectiveAuthorship / preprint / 2022PaperSuperlinear Precision and Memory in Simple Population CodesAuthorship / preprint / 2020PaperTraining recurrent networks to generate hypotheses about how the brain solves hard navigation problemsAuthorship / preprint / 2016

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