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

A Few Thoughts on Deep Network Approximation

Wed, Aug 12, 2020, 12:00 pm

Deep network approximation is a powerful tool of function approximation via composition. We will present a few new thoughts on deep network approximation from the point of view of scientific computing in practice: given an arbitrary width and depth of neural networks, what is the optimal approximation rate of various function...

Location: https://www.oneworldml.org/upcoming-events
Speaker(s):

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

Data Wrangling: How to Keep Your Data Workflows Orderly and Efficient

This webinar will provide several practical considerations to help you better manage your research data between the points of collection and analysis. We will review the principles of open research and cover best practices for documentation and metadata generation amidst collation, aggregation, and cleaning tasks.

Tags: Seminars

Tradeoffs between Robustness and Accuracy

Standard machine learning produces models that are highly accurate on average but that degrade dramatically when the test distribtion deviates from the training distribution. While one can train robust models, this often comes at the expense of standard accuracy (on the training distribution).

Location: https://www.oneworldml.org/upcoming-events
Speaker(s):

Thematic Day on the Mean Field Training of Deep Neural Networks

12pm: Roberto I. Oliveira – TBA 

1pm: Konstantinos Spiliopoulos  - Mean field limits of neural networks: typical behavior and fluctuations

2pm: Huy Tuan Pham - A general framework for the mean field limit of multilayer neural networks

Location: https://www.oneworldml.org/thematic-days/mean-field-training-of-multi-layer-networks

Managing Research Data

This webinar will go over tips on how to keep track of your data files more efficiently, better organize your data files, and how to manage your data, code and other research materials, to save yourself headaches down the road.

MSML2020 - Mathematical and Scientific Machine Learning Conference

VIRTUAL Conference

The objective of this annual conference series is to promote the study of theory and algorithms of machine learning and applications in scientific and engineering disciplines such as physics, chemistry, material sciences, etc.

On the foundations of computational mathematics, Smale’s 18th problem and the potential limits of AI

There is a profound optimism on the impact of deep learning (DL) and AI in the sciences with Geoffrey Hinton concluding that 'They should stop educating radiologists now'. However, DL has an Achilles heel: it is universally unstable so that small changes in the initial data can lead to large errors in the final result. This has been documented...

Location: https://www.oneworldml.org/home
Speaker(s):
Tags: Seminars

Molecular Simulation with Machine Learning

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

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/(...

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...

Speaker(s):
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/
Speaker(s):
Tags: Seminars

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