Spatial analysis | Data mining
Spatial embedding is one of feature learning techniques used in spatial analysis where points, lines, polygons or other spatial data types. representing geographic locations are mapped to vectors of real numbers. Conceptually it involves a mathematical embedding from a space with many dimensions per geographic object to a continuous vector space with a much lower dimension. Such embedding methods allow complex spatial data to be used in neural networks and have been shown to improve performance in spatial analysis tasks (Wikipedia).
Graph Neural Networks, Session 6: DeepWalk and Node2Vec
What are Node Embeddings Overview of DeepWalk Overview of Node2vec
From playlist Graph Neural Networks (Hands-on)
Jasna UrbanΔiΔ (11/03/21):Optimizing Embedding using Persistence
Title: Optimizing Embedding using Persistence Abstract: We look to optimize Takens-type embeddings of a time series using persistent (co)homology. Such an embedding carries information about the topology and geometry of the dynamics of the time series. Assuming that the input time series
From playlist AATRN 2021
From playlist Week 4: Vector Semantics and Embeddings
Word embeddings quantify 100 years of gender & ethnic stereotypes-- Nikhil Garg (NLP video 13)
Stanford researcher Nikhil Garg gives a guest lecture on his work: Word embeddings are a powerful machine-learning framework that represents each English word by a vector. The geometric relationship between these vectors captures meaningful semantic relationships between the corresponding
From playlist fast.ai Code-First Intro to Natural Language Processing
Word embeddings are one of the coolest things you can do with Machine Learning right now. Try the web app: https://embeddings.macheads101.com Word2vec paper: https://arxiv.org/abs/1301.3781 GloVe paper: https://nlp.stanford.edu/pubs/glove.pdf GloVe webpage: https://nlp.stanford.edu/proje
From playlist Machine Learning
Rasa Algorithm Whiteboard - Understanding Word Embeddings 1: Just Letters
We're making a few videos that highlight word embeddings. Before training word embeddings we figured it might help the intuition if we first trained some letter embeddings. It might suprise you but the idea with an embedding can also be demonstrated with letters as opposed to words. We're
From playlist Algorithm Whiteboard
Virtual EmberConf 2020: An Ember Dev's Guide to CSS Grid by James Steinbach
An Ember Dev's Guide to CSS Grid by James Steinbach There's plenty of buzz about CSS Grid, but from a distance, it can seem intimidating - especially for developers who don't often write CSS. Grid feels daunting for good reason: the Grid layout module added over 30 new properties, values,
From playlist EmberConf 2020
Thomas Baumgarte (2) - Numerical relativity: Mathematical formulation
PROGRAM: NUMERICAL RELATIVITY DATES: Monday 10 Jun, 2013 - Friday 05 Jul, 2013 VENUE: ICTS-TIFR, IISc Campus, Bangalore DETAL Numerical relativity deals with solving Einstein's field equations using supercomputers. Numerical relativity is an essential tool for the accurate modeling of a wi
From playlist Numerical Relativity
Intro To Graph Neural Networks || Kefei Hu
A graph is a data structure consisting of two components, nodes and edges. It is useful for modelling relationships and interactions between interconnected entities. Many types of data can naturally be represented this way, such as social networks, molecule interactions or even websites.
From playlist Machine Learning
Make-A-Video: Text-To-Video Generation Without Text-Video Data | Paper Explained
π Find out how to get started using Weights & Biases π http://wandb.me/ai-epiphany π¨βπ©βπ§βπ¦ Join our Discord community π¨βπ©βπ§βπ¦ https://discord.gg/peBrCpheKE In this video I cover the latest text-to-video paper from Meta: "Make-A-Video: Text-To-Video Generation Without Text-Video Data". I
From playlist Video
Rasa Reading Group: Pay Attention to MLPs
This week we'll be reading the unpublished preprint "'Pay Attention to MLPs" (that's "multilayer perceptrons", the classic minimal deep learning architecture) by Hanxiao Liu, Zihang Dai, David R. So, Quoc V. Le from Google Brain. It proposes replacing attention in transformers with multila
From playlist Rasa Reading Group
Symplectic embeddings, integrable systems and billiards - Vinicius Ramos
Symplectic Dynamics/Geometry Seminar Topic: Symplectic embeddings, integrable systems and billiards Speaker: Vinicius Ramos Affiliation: Member, School of Mathematics Date: January 27, 2020 For more video please visit http://video.ias.edu
From playlist Mathematics
The Four-Color Theorem and an Instanton Invariant for Spatial Graphs I - Peter Kronheimer
Peter Kronheimer Harvard University October 13, 2015 http://www.math.ias.edu/seminars/abstract?event=83214 Given a trivalent graph embedded in 3-space, we associate to it an instanton homology group, which is a finite-dimensional Z/2 vector space. The main result about the instanton hom
From playlist Geometric Structures on 3-manifolds
Workshop 1 "Operator Algebras and Quantum Information Theory" - CEB T3 2017 - M.Musat
Magdalena Musat (University of Copenhagen) / 14.09.17 Title: Quantum correlations, tensor norms, and factorizable quantum channels Abstract: In joint work with Haagerup, we established in 2015 a reformulation of the Connes embedding problem in terms of an asymptotic property of quantum c
From playlist 2017 - T3 - Analysis in Quantum Information Theory - CEB Trimester
Knots, three-manifolds and instantons β Peter Kronheimer & Tomasz Mrowka β ICM2018
Plenary Lecture 11 Knots, three-manifolds and instantons Peter Kronheimer & Tomasz Mrowka Abstract: Over the past four decades, input from geometry and analysis has been central to progress in the field of low-dimensional topology. This talk will focus on one aspect of these developments
From playlist Plenary Lectures
Will Rule 30 Help Me Find Gold?
The thesis is that geological mineralising systems may be considered as chemical reactors, incorporating interactions among deformation, heat, fluid flow and chemical reactions. These physical phenomena may be described by nonlinear dynamics, with possibly chaotic resulting behaviours. The
From playlist Wolfram Technology Conference 2020
Thomas Baumgarte (3) - Numerical relativity: Mathematical formulation
PROGRAM: NUMERICAL RELATIVITY DATES: Monday 10 Jun, 2013 - Friday 05 Jul, 2013 VENUE: ICTS-TIFR, IISc Campus, Bangalore DETAL Numerical relativity deals with solving Einstein's field equations using supercomputers. Numerical relativity is an essential tool for the accurate modeling of a wi
From playlist Numerical Relativity
Exploring Symplectic Embeddings and Symplectic Capacities
Speakers o Alex Gajewski o Eli Goldin o Jakwanul Safin o Junhui Zhang Project Leader: Kyler Siegel Abstract: Given a domain (e.g. a ball) in Euclidean space, we can ask what is its volume. We can also ask when one domain can be embedded into another one without distorting volumes. These
From playlist 2019 Summer REU Presentations
How to get started with Graph ML? (Blog walkthrough)
β€οΈ Become The AI Epiphany Patreon β€οΈ βΊ https://www.patreon.com/theaiepiphany β¬β¬β¬β¬β¬β¬β¬β¬β¬β¬β¬β¬β¬β¬β¬β¬β¬β¬β¬β¬β¬β¬β¬β¬ In this video, I walk you through my blog on getting started with Graph ML. I talk about research, learning, cool Graph ML apps, resources to get you started, my GAT project, and beyond!
From playlist Graph Neural Nets