# Upcoming Events

*Princeton University is actively monitoring the situation around coronavirus (COVID-19) and the evolving guidance from government and health authorities. The latest guidance for Princeton members and visitors is available on the University’s Emergency Management website. *

No upcoming events found.

## Events Archive

### Introduction to NumPy with Vineet Bansal, Research Computing Bootcamp

### Reproducible Research Reports with R Markdown with Daisy Huang, Research Computing Bootcamp

### Intro to Data Analysis Using R w/ Brian Arnold & Andrzej Zuranski (Schmidt DataX), Research Computing Bootcamp

### Research Computing Bootcamp, Jan. 19-29, 2021, Registration Now Open

The Princeton Institute for Computational Science & Engineering (PICSciE) and OIT Research Computing , along with the Center for Statistics and Machine Learning(link is external), are announcing a...

### Deep Networks from First Principles

### Breaking the Sample Size Barrier in Statistical Inference and Reinforcement Learning

A proliferation of emerging data science applications require efficient extraction of information from complex data. The unprecedented scale of relevant features, however, often overwhelms the volume of available samples, which dramatically complicates statistical inference and decision making.

### HEE Seminar- Taylor Faucett-UCI-Physics Learning from Machines Learning

Machine Learning methods are extremely powerful but often function as black-box problem solvers, providing improved performance at the expense of clarity. Our work describes a new machine learning approach which translates the strategy of a deep neural network into simple functions that are meaningful and intelligible to the physicist, without...

### Using Code Ocean in the Sciences and Engineering: Bringing computational reproducibility to your research collaborations

Computational analyses are playing an increasingly central role in research. However, many researchers have not received training in best practices and tools for reproducibly managing and sharing their code and data. This is a step-by-step, practical workshop on managing your research code and data for computationally reproducible collaboration...

### Conditional Sampling with Monotone GANs: Modifying Generative Models to Solve Inverse Problems

The One World Seminar Series on the Mathematics of Machine Learning is an online platform for research seminars, workshops and seasonal schools in theoretical machine learning.