Upcoming Events
Lunch available beginning at 12:15 PM
Speaker to begin at 12:30 PM
This is an informal event.
This event is for seniors only, with a maximum capacity of 15-20 students.
Lunch available beginning at 12:15 PM
Speaker to begin at 12:30 PM
Graduate students completing certificates in Computational Science & Engineering and Statistics & Machine Learning will give seminars on their dissertation research. Each seminar will be approximately 20 minutes including time for questions from the audience. The event is open to the campus community.
Lunch available beginning at 12:15 PM
Speaker to begin at 12:30 PM
Events Archive
Abstract: Despite their increasing sophistication, modern robotic systems still struggle to operate safely and reliably around people in uncertain open-world situations, a key bottleneck to adoption that is perhaps best exemplified by the growing public distrust of early autonomous driving technology. At the same time,…
Lunch available from 12:15pm.
Please RSVP to [email protected] by February 22nd to participate in lunch.
If you wish to participate via Zoom Webinar, we ask that you please register prior to attending.
RSVP to [email protected]
Lunch available beginning at 12:15 PM
Speaker to begin at 12:30 PM
The Center for Statistics and Machine Learning is offering a three hour Wintersession workshop which aims to increase awareness of how machine learning could aid faculty, postdoc, and student research. No detailed prior knowledge of machine learning is assumed. The workshop will begin with an overview of crucial machine learning ideas and…
The fusion of deep learning and optimization has the potential to deliver outcomes for engineering applications that the two technologies cannot achieve independently. This talk illustrates this potential with the concept of optimization proxy, a differentiable program that can produce feasible (or near-feasibel) and near-optimal solutions to…
A new seminar hosted jointly between Physics and ORFE focusing on interdisciplinary work at the intersection of physics and machine learning.
What? A seminar series highlighting research on both physics-inspired approaches to understanding ML and the use of ML for physics applications
- AffiliationCCA, Flatiron Institute
- AffiliationVector Institute for Artificial Intelligence
- AffiliationUniversity of California San Diego
- AffiliationMIT Physics
- AffiliationPrinceton Physics and Neuroscience
Abstract:
Machine learning designs approaches that transform data to predictions or estimations. The standard paradigm often assumes these data are objectively generated from distributions, without being affected by any human factors. However, this paradigm ceases to be true when our predictions or estimated…
This webinar is open to all via Zoom.
Dozens of policy proposals and interventions have attempted to address actual and potential cases of algorithmic bias, particularly in systems that have consequential effects on people’s lives. While these proposals commonly…
A new seminar hosted jointly between Physics and ORFE focusing on interdisciplinary work at the intersection of physics and machine learning.
What? A seminar series highlighting research on both physics-inspired approaches to understanding ML and the use of ML for physics applications
- AffiliationCCA, Flatiron Institute
- AffiliationVector Institute for Artificial Intelligence
- AffiliationUniversity of California San Diego
- AffiliationMIT Physics
- AffiliationPrinceton Physics and Neuroscience
Recent breakthroughs in Artificial Intelligence (AI) have produced a new class of neural networks called Large Language Models (LLMs) that demonstrate a remarkable capability to generate fluent, plausible responses to prompts posed in natural language. While LLMs have already revolutionized certain industry applications, the recent debut of…
- Wai Chee DimockAffiliationWilliam Lampson Professor Emeritus of American Studies and English, Yale University; Research Affiliate, Harvard University Center for the Environment
- Meredith MartinAffiliationEnglish; Center for Digital Humanities