Upcoming Events

Upcoming Events

Capitalizing on Generative AI: Guided Diffusion Models Towards Generative Optimization
Tue, Apr 23, 2024, 12:15 pm1:20 pm

Lunch available beginning at 12:15 PM
Speaker to begin at 12:30 PM

Abstract: Diffusion models represent a significant breakthrough in generative AI, operating by progressively transforming random noise distributions into structured outputs, with adaptability for specific tasks through guidance or fine…

Location
Bendheim House 103
Speaker
Joint PICSciE & CSML Graduate Certificate Colloquium
Wed, Apr 24, 2024, 1:00 pm4:30 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. 

Location
Convocation Room, 113 Friend Center, Olden Street
CSML Machine Learning Lunchtime Seminar Series
Tue, May 7, 2024, 12:15 pm1:20 pm

Lunch available beginning at 12:15 PM
Speaker to begin at 12:30 PM

Contributions to and/or sponsorship of any event does not constitute departmental or institutional endorsement of the specific program, speakers or views presented.

Location
Bendheim House 103
Speaker

Events Archive

Dinner with a Professor (CSML Seniors only)

This event is for seniors only, with a maximum capacity of 15-20 students.

Contributions to and/or sponsorship of any event does not constitute departmental or institutional endorsement of the specific program, speakers or views presented.

Machine Learning for Structural Biology

Lunch available beginning at 12:15 PM
Speaker to begin at 12:30 PM

Abstract: Structural biology has been transformed by breakthroughs in deep learning methods for protein structure prediction. In parallel, advances in cryo-electron microscopy (cryo-EM) have produced new opportunities to study the structure…

Location
Bendheim House 103
Speaker
Sushi with Sophomores (Sophomore Open House)

This is an informal event.

Location
CSML Library Lounge 104
CSML Machine Learning Lunchtime Seminar Series

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,…

Location
Bendheim House 103
Towards more human-like learning in machines: Bridging the data and generalization gaps

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.

Location
Computer Science 105
Speaker
CSML Machine Learning Lunchtime Seminar Series

RSVP to [email protected]

Lunch available beginning at 12:15 PM
Speaker to begin at 12:30 PM

Location
Bendheim House 103
Speaker
Winter Session: What is Machine Learning, and Can it Aid my Research?

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…

Fusing Deep Learning and Optimization

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…

Location
101 Sherrerd Hall
Speaker
Machine Learning in Physics

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

Location
Jadwin Hall A10
Speakers
Algorithms and Incentives in Machine Learning

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…

Location
B205 Engineering Quadrangle
Speaker