Media Summary: From Local Views to Global Embedding: Methods in Bottom-up Manifold Data points, equations, and analysis are only part of a day in the life of a mathematician. UC San Diego's Abstract: In many applications, constructing kernel matrices or pairwise distance matrices can be prohibitively expensive. This can ...

Alex Cloninger Deep Learning Based - Detailed Analysis & Overview

From Local Views to Global Embedding: Methods in Bottom-up Manifold Data points, equations, and analysis are only part of a day in the life of a mathematician. UC San Diego's Abstract: In many applications, constructing kernel matrices or pairwise distance matrices can be prohibitively expensive. This can ... Dr. Paul Lessard and his collaborators have written a paper on "Categorical Detecting differences and building classifiers between distributions, given only finite samples, are important tasks in a number of ... Many scientific problems involve invariant structures, and

New Technologies in Mathematics Seminar 10/8/2025 Speaker: Shortform link: ===== My name is Artem, I'm a neuroscience PhD student at Harvard University.

Photo Gallery

Alex Cloninger - Deep Learning Based Two Sample Tests with Small Data and Small Networks
1W-MINDS, Oct. 16:  Alex Cloninger (University of California, San Diego),  From Local Views to...
Alex Cloninger - Linearized Optimal Transport to Predict Evolution of Stochastic Particle Systems
Meet a Mathematician with Alex Cloninger - Science Like Me
Data Representation Learning from a Single Pass of the Data - Alex Cloninger - FFT Apr. 4th, 2022
Alex Cloninger, Fast Statistical and Geometric Distances Between Families of Distr., 2020.11.10
WE MUST ADD STRUCTURE TO DEEP LEARNING BECAUSE...
Alexander Cloninger: Efficient Distribution Classification (Linearized Optimal Transport Embeddings)
Incorporating Invariance to Reduce the Complexity of Parametric Models, Alex Cloninger@UCSD
Alex Damian | Understanding Optimization in Deep Learning with Central Flows
Data Representation Learning from a Single Pass of the Data
The Most Important Algorithm in Machine Learning
View Detailed Profile
Alex Cloninger - Deep Learning Based Two Sample Tests with Small Data and Small Networks

Alex Cloninger - Deep Learning Based Two Sample Tests with Small Data and Small Networks

Alex Cloninger

1W-MINDS, Oct. 16:  Alex Cloninger (University of California, San Diego),  From Local Views to...

1W-MINDS, Oct. 16: Alex Cloninger (University of California, San Diego), From Local Views to...

From Local Views to Global Embedding: Methods in Bottom-up Manifold

Alex Cloninger - Linearized Optimal Transport to Predict Evolution of Stochastic Particle Systems

Alex Cloninger - Linearized Optimal Transport to Predict Evolution of Stochastic Particle Systems

Recorded 15 July 2025.

Meet a Mathematician with Alex Cloninger - Science Like Me

Meet a Mathematician with Alex Cloninger - Science Like Me

Data points, equations, and analysis are only part of a day in the life of a mathematician. UC San Diego's

Data Representation Learning from a Single Pass of the Data - Alex Cloninger - FFT Apr. 4th, 2022

Data Representation Learning from a Single Pass of the Data - Alex Cloninger - FFT Apr. 4th, 2022

Abstract: In many applications, constructing kernel matrices or pairwise distance matrices can be prohibitively expensive. This can ...

Alex Cloninger, Fast Statistical and Geometric Distances Between Families of Distr., 2020.11.10

Alex Cloninger, Fast Statistical and Geometric Distances Between Families of Distr., 2020.11.10

Speaker:

WE MUST ADD STRUCTURE TO DEEP LEARNING BECAUSE...

WE MUST ADD STRUCTURE TO DEEP LEARNING BECAUSE...

Dr. Paul Lessard and his collaborators have written a paper on "Categorical

Alexander Cloninger: Efficient Distribution Classification (Linearized Optimal Transport Embeddings)

Alexander Cloninger: Efficient Distribution Classification (Linearized Optimal Transport Embeddings)

Detecting differences and building classifiers between distributions, given only finite samples, are important tasks in a number of ...

Incorporating Invariance to Reduce the Complexity of Parametric Models, Alex Cloninger@UCSD

Incorporating Invariance to Reduce the Complexity of Parametric Models, Alex Cloninger@UCSD

Many scientific problems involve invariant structures, and

Alex Damian | Understanding Optimization in Deep Learning with Central Flows

Alex Damian | Understanding Optimization in Deep Learning with Central Flows

New Technologies in Mathematics Seminar 10/8/2025 Speaker:

Data Representation Learning from a Single Pass of the Data

Data Representation Learning from a Single Pass of the Data

Date Presented: 06/24/2022 Speaker:

The Most Important Algorithm in Machine Learning

The Most Important Algorithm in Machine Learning

Shortform link: https://shortform.com/artem ===== My name is Artem, I'm a neuroscience PhD student at Harvard University.

Understanding Deep Learning Research Tutorial - Theory, Code and Math

Understanding Deep Learning Research Tutorial - Theory, Code and Math

If you've ever felt intimidated by