embedding – Page 4 – Andrew Fairless, Ph.D.

What I Read: Beyond Message Passing, Graph Neural Networks

By Andrew Fairless on June 6, 2022May 23, 2022

https://thegradient.pub/graph-neural-networks-beyond-message-passing-and-weisfeiler-lehman/ Beyond Message Passing: a Physics-Inspired Paradigm for Graph Neural NetworksMichael Bronstein07.May.2022 “…the “node and edge-centric” mindset of current graph deep learning schemes imposes strong limitations… we propose physics-inspired “continuous”Continue readingWhat I Read: Beyond Message Passing, Graph Neural Networks

What I Read: Graph Neural Networks, Differential Geometry, Algebraic Topology

By Andrew Fairless on January 3, 2022December 11, 2021

https://towardsdatascience.com/graph-neural-networks-through-the-lens-of-differential-geometry-and-algebraic-topology-3a7c3c22d5f Graph Neural Networks through the lens of Differential Geometry and Algebraic TopologyMichael Bronstein “Differential geometry and algebraic topology are not encountered very frequently in mainstream machine learning… tools fromContinue readingWhat I Read: Graph Neural Networks, Differential Geometry, Algebraic Topology

What I Read: Dense Vectors

By Andrew Fairless on December 14, 2021November 16, 2021

https://www.pinecone.io/learn/dense-vector-embeddings-nlp/ Dense Vectors: Capturing Meaning with CodeJames BriggsData Scientist “But since the days of word2vec, developments in representing language have advanced at ludicrous speeds. This article will explore why weContinue readingWhat I Read: Dense Vectors

What I Read: demystifying graph deep learning

By Andrew Fairless on August 30, 2021August 17, 2021

https://ericmjl.github.io/essays-on-data-science/machine-learning/graph-nets/ An attempt at demystifying graph deep learningEric Ma “There are a ton of great explainers of what graph neural networks are. However, I find that a lot of themContinue readingWhat I Read: demystifying graph deep learning

What I Read: Zero-Shot Learning

By Andrew Fairless on May 6, 2021April 13, 2021

https://www.kdnuggets.com/2021/04/zero-shot-learning.html Zero-Shot Learning: Can you classify an object without seeing it before?Developing machine learning models that can perform predictive functions on data it has never seen before has become anContinue readingWhat I Read: Zero-Shot Learning

What I Read: Deep Learning Recommendation Models

By Andrew Fairless on April 24, 2021April 10, 2021

https://www.kdnuggets.com/2021/04/deep-learning-recommendation-models-dlrm-deep-dive.html Deep Learning Recommendation Models (DLRM): A Deep DiveBy Nishant Kumar, Data Science Professional. “This deep dive article presents the architecture and deployment issues experienced with the deep learning recommendationContinue readingWhat I Read: Deep Learning Recommendation Models

What I Read: Why I’m lukewarm on graph neural networks

By Andrew Fairless on March 10, 2021March 7, 2021

https://www.singlelunch.com/2020/12/28/why-im-lukewarm-on-graph-neural-networks/ Why I’m lukewarm on graph neural networksMatt RangerFebruary 16, 2020 “I’m only lukewarm on Graph Neural Networks (GNNs)…. I think some progress can come of this research, but we’reContinue readingWhat I Read: Why I’m lukewarm on graph neural networks

What I Read: Approximate Nearest Neighbor Search in Vespa

By Andrew Fairless on February 21, 2021January 26, 2021

https://blog.vespa.ai/approximate-nearest-neighbor-search-in-vespa-part-1/ Approximate Nearest Neighbor Search in Vespa – Part 1Geir StorliPrinciple Vespa Engineer “Searching for the nearest neighbors of a data point in a high dimensional vector space is anContinue readingWhat I Read: Approximate Nearest Neighbor Search in Vespa

What I Read: Building a Gigascale ML Feature Store

By Andrew Fairless on February 18, 2021January 18, 2021

https://doordash.engineering/2020/11/19/building-a-gigascale-ml-feature-store-with-redis/ Building a Gigascale ML Feature Store with Redis, Binary Serialization, String Hashing, and CompressionNovember 19, 2020 21 Minute Read Data, Machine Learning 36Arbaz Khan Zohaib Sibte Hassan “When aContinue readingWhat I Read: Building a Gigascale ML Feature Store

What I Read: HuggingFace Transformers

By Andrew Fairless on February 18, 2021January 18, 2021

https://medium.com/georgian-impact-blog/how-to-incorporate-tabular-data-with-huggingface-transformers-b70ac45fcfb4 How to Incorporate Tabular Data with HuggingFace TransformersGeorgianOct 23 “At Georgian, we find ourselves working with supporting tabular feature information as well as unstructured text data. We found thatContinue readingWhat I Read: HuggingFace Transformers

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