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Analyzing How Neural Networks Manipulate the Shape of Data, Reuel Williams, UG '24 (9C22A282)

Understanding the mathematical shape of data that neural networks learn from can provide valuable insights into their inner workings. In my senior thesis, I delve into this concept using a…

From  Research Princeton Research Day 3 likes 39 plays

Wald, Robert, March 18, 2024, "Black Holes Decohere Quantum Superpositions"

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JPP14March2024_GZank

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OLTP05December2023_DEremin

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TS08November2023_MFalessi

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Bradford Seminar: 'Harmonizing Forces: A Global Quest to Tackle the Water and Climate Crisis Through Sustainable Development Goals"

In an era defined by environmental challenges, the world is witnessing a transformative journey undertaken in parallel by global corporations, non-governmental organizations, and government…

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Jimenez-Rosales, Alejandra, February 10, 2023, "Modeling Polarisation Signatures of Sgr A* Flares at Event Horizon Scales"

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von Fellenberg, Sabastiano, February 10, 2023 "A Characteristic Flare Shape for NIR and X-Ray Flares of Sgr A*"

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OURSIP Intern - Ethan Sample

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Ines Montani, Solutions for Advanced NLP for Diverse Languages, May 12, 2022

This event is part of the New Languages for NLP: Building Linguistic Diversity in the Digital Humanities Institute, in partnership with DARIAH-EU and generously supported by a grant from the National…

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ROTC 2022

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cos326-2020-13-03-ho-rep-inv

Reasoning About Modular Programs: Part 3: More Representation Invariants

From  Daniel Macleod 0 likes 227 plays

cos326-2020-06-01-abstract-syntax

Implementing Ocaml in Ocaml: Part 1: Representing Abstract Syntax

From  Daniel Macleod 0 likes 317 plays

Ward, Rachel "Learning the Learning Rate in Stochastic Gradient Descent" May 15, 2018

PCTS "Bridging Mathematical Optimization, Information Theory and Data Science"

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JKrommes, AST-554, Lecture 17, "Runaways, Current Drive, Braginskii 1", 15APR2014

Professor John Krommes, Princeton University

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The Productive Scholar: John LeMasney on Sketchup

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