Semanlink - Science ; Arxiv Doc AND Representation learning

[1410.5859] Towards a Model Theory for Distributed Representations

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2021-06-10 About

[2010.00402] From Trees to Continuous Embeddings and Back: Hyperbolic Hierarchical Clustering

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2020-10-03 About

[1807.00082] Amanuensis: The Programmer's Apprentice

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**The use of natural language to facilitate communication
between the expert programmer and apprentice AI system.**

> an overview of the material covered in a course taught at Stanford in the spring quarter of 2018. The course draws upon **insight from cognitive and systems neuroscience to implement hybrid connectionist and symbolic reasoning systems** that leverage and extend the state of the art in machine learning **by integrating human and machine intelligence**. As a concrete example we focus on digital assistants that learn from continuous dialog with an expert software engineer while providing initial value as powerful analytical, computational and mathematical savants.

> [#Dehaene](/tag/stanislas_dehaene)'s work extends the [#Global Workspace Theory](/tag/global_workspace_theory) of Bernard Baars. Dehaene’s version of the theory combined with Yoshua Bengio’s concept of a [#consciousness prior](/tag/consciousness_prior.html) and deep reinforcement learning suggest a model for constructing and maintaining the cognitive states that arise and persist during complex problem solving.

2019-11-12 About

[1910.03524] Beyond Vector Spaces: Compact Data Representation as Differentiable Weighted Graphs

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2019-10-09 About

[1907.03950] Learning by Abstraction: The Neural State Machine

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2019-07-10 About

[1705.08039] Poincaré Embeddings for Learning Hierarchical Representations

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2017-12-16 About

[1709.08568] The Consciousness Prior

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2017-09-29 About