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Claudia Zhu
Claudia Zhu

61 Followers

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hello and welcome to my page my name is Claudia Zhu and I am a new grad from Penn with a degree in Computer Science. I am looking for cool opportunities involving algorithms, math, cryptography, and/or machine learning. Intro to come, but feel free to check out some of my…

1 min read

1 min read


Feb 17, 2021

ML asks “wHY?!”

Review of MIT’s WHY! Conceptual Contributions It is an interesting and challenging question to resolve how we determine the “why” behind an image. It is posited that it is a result of “Theory of the Mind” and psychophysics researchers hypothesize that our capacity to reliably infer another person’s motivation stems from our…

Machine Learning

4 min read

ML asks “wHY?!”
ML asks “wHY?!”
Machine Learning

4 min read


Feb 17, 2021

Deep Dive into DeViSE

Review of DeViSE — Conceptual Contributions In DeViSE, the authors tackle the issue that visual recognition systems are often limited in their ability to scale to large numbers of classification categories in part due to difficulty in acquiring such a balanced dataset as well as the traditionally rigid nature of classification within defined classes. The authors…

4 min read

Deep Dive into DeViSE
Deep Dive into DeViSE

4 min read


Feb 17, 2021

Neural Baby Talk

Review of this article Conceptual Contributions This paper aims to improve image captioning, which is one of the primary challenges in the intersection of CV and NLP. Tangible process improves applications from aiding visually impaired users to human computer interaction. …

4 min read

Neural Baby Talk
Neural Baby Talk

4 min read


Sep 30, 2020

Knowledge Graphs and NLP

Overview of From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions — Semantic interpretation, or making inferences on the meaning of atext is a fundamental step in language understanding. Drawing from our human ability to envisionmental images when prompted by a description, this paper introduces a novel approach for automaticallydenoting similarities between descriptions of everyday situations via sets of images and captions…

Machine Learning

3 min read

Knowledge Graphs and NLP
Knowledge Graphs and NLP
Machine Learning

3 min read


Aug 15, 2020

The World’s Biggest Game of Memory

An Overview of Segmenting Scenes by Matching Image Composites Introduction One of the major goals in computer vision is semantic object segmentation, which is essentially identifying different objects that have semantic meaning (toothbrush or tree) within an image. …

Computer Vision

11 min read

The World’s Biggest Game of Memory
The World’s Biggest Game of Memory
Computer Vision

11 min read


Published in Analytics Vidhya

·Oct 29, 2019

Eyes on the Sphere 👀

An Overview of Spherical CNNs, Best Paper Award in the 2018 ICLR Conference by Taco Cohen and his team! — Convolutional Neural Networks (CNNs), which is a class of deep learning neural networks, have become the go-to method for 2D image detection/classification as it produce accurate results without taking too much computing power or time. You can find out more about how it works here and the original motivation, which…

Machine Learning

7 min read

Eyes on the Sphere 👀
Eyes on the Sphere 👀
Machine Learning

7 min read


Jun 14, 2019

One Model’s Trash is Another’s Treasure

Review of Microsoft’s Deep Residual Learning for Image Recognition — Note: This paper was a bit difficult for me and I relied heavily on other sources to help me understand the material. …

Machine Learning

4 min read

One Model’s Trash is Another’s Treasure
One Model’s Trash is Another’s Treasure
Machine Learning

4 min read


Jun 13, 2019

Tidal Motions of Causality

A Review of Joseph Halpern’s A Modification of the Halpern-Pearl Definition of Causality Waves: An Introduction Just as the waves ebb and flow, the principles of causality, cause and effect push and pull the world around us into the way that it is. Despite the fact that causality in principle is something that…

Artificial Intelligence

7 min read

Artificial Intelligence

7 min read


Apr 11, 2019

Complexity and Uncertainty

Finding a Balance Using First Order Logic and Markov Random Fields — There is a huge need in computer science, specifically in developing technologies of artificial intelligence and machine learning for representing knowledge as well as making predictions on the world/for future. There are two primary approaches to solving this problem: There is the logical mindset where we approach this problem through…

Machine Learning

3 min read

Markov Logic Networks (MLN) Briefly
Markov Logic Networks (MLN) Briefly
Machine Learning

3 min read

Claudia Zhu

Claudia Zhu

61 Followers

Works, Observations, and Thoughts | Student at UPenn linkedin.com/in/claudiazhu

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