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

Molecular Simulation with Machine Learning

Mon, Jul 13, 2020 (All day) to Tue, Jul 14, 2020 (All day)

A two-day virtual workshop covering theory and hands-on tutorials on the software package for molecular simulation with machine learning (ML) tools developed at the Computational Chemical Science Center “Chemistry in Solution and at Interfaces” (http://chemlabs.princeton.edu/ccsc/(...

Molecular Simulation with Machine Learning

Mon, Jul 13, 2020 (All day) to Tue, Jul 14, 2020 (All day)

A two-day virtual workshop covering theory and hands-on tutorials on the software package for molecular simulation with machine learning (ML) tools developed at the Computational Chemical Science Center “Chemistry in Solution and at Interfaces” (http://chemlabs.princeton.edu/ccsc/(...

DataX Workshop Series: Synthetic Control Methods | Day 1 (POSTPONED UNTIL 2021)

Fri, Sep 11, 2020, 2:00 pm

This event has been postponed until 2021. More information will be provided when available.

DataX Workshop Series: Synthetic Control Methods | Day 2 (POSTPONED UNTIL 2021)

Sat, Sep 12, 2020, 8:00 am

This event has been postponed until 2021. More information will be provided when available.

Events Archive

Trainability and accuracy of artificial neural networks

The methods and models of machine learning (ML) are rapidly becoming de facto tools for the analysis and interpretation of large data sets. Complex classification tasks such as speech and image recognition, automatic translation, decision making, etc. that were out of reach a decade ago are now routinely performed by computers with a high...

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Tags: Seminars

Towards a mathematical understanding of supervised learning: What we know and what we don't know

Two of the biggest puzzles in machine learning are: Why is it so successful and why is it quite fragile? This talk will present a framework for unraveling these puzzles from the perspective of approximating functions in high dimensions.

Location: https://www.oneworldml.org/
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Tags: Seminars

Microsoft Azure Two-Part Cloud Computing Workshop

This is a hands-on 2-hour applied workshop, where attendees will learn new concepts by building their solutions on Azure and interacting directly with the instructors.

Reimagining Digitized Newspapers with Machine Learning

The 16 million digitized historic newspaper pages within Chronicling America, a joint initiative by the Library of Congress and the NEH, represent an incredibly rich resource for a wide range of users. Historians, journalists, genealogists, students, and members of the American public explore...

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2020 CSML Virtual Undergraduate Poster Session

Independent work posters and papers are due on May 12th at 12pm EST. Please check your email for details

Check out an article on 2019's poster session here.

Princeton Research Day

To keep everyone safe and support social distancing, Princeton Research Day will not be held in person this year. We are exploring other possibilities with input from the campus community, and expect to announce those decisions by early April.

Dinner with a Professor

More information forthcoming on this event.

For an article on the previous year's dinner, read here.

Location: Prospect House

FPGA Training with Intel

Research Computing recently installed four Intel FPGAs on the Della cluster. After attending this workshop you should have the skills needed to start using these devices.
Location: 120 Lewis Science Library
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NVIDIA Workshop: Fundamentals of Deep Learning for Computer Vision

Learn deep learning techniques for a range of computer vision tasks, including training and deploying neural networks.
Location: 120 Lewis Science Library

Running and Analyzing Large-scale Psychology Experiments

Psychology has traditionally been a laboratory discipline, focused on small-scale experiments conducted in person. However, recent technological innovations have made it possible to collect far more data from far more people than ever before.

Location: 399 Julis Romo Rabinowitz
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