Ian Covert (@ianccovert) 's Twitter Profile
Ian Covert

@ianccovert

Postdoc @Stanford, previously @uwcse @GoogleAI and @Columbia. Interested in deep learning and explainable AI

ID: 832685054027378688

linkhttps://iancovert.com/ calendar_today17-02-2017 20:16:02

40 Tweet

299 Followers

145 Following

Parul Pandey (@pandeyparul) 's Twitter Profile Photo

Check out this course on #XAI by Su-In Lee & Ian Covert. Very practical and nicely curated. Also points to some great papers on the topic. The course covers a broad set of principles and techniques. Slides are available here: buff.ly/3Dasssm #ResponsibleAI

Check out this course on #XAI by <a href="/suinleelab/">Su-In Lee</a>
 &amp;  <a href="/ianccovert/">Ian Covert</a>. Very practical and nicely curated. Also points to some great papers on the topic. The course covers a broad set of principles and techniques. Slides are available here: buff.ly/3Dasssm  
 #ResponsibleAI
Chris Lin (@chrislin97) 's Twitter Profile Photo

We have an upcoming paper at ICLR 2023 on a new feature attribution method for explaining representations learned by unsupervised models! arxiv.org/abs/2210.00107 This was joint work with the fantastic Hugh Chen Chanwoo Kim and my advisor Su-In Lee. (1/n)

We have an upcoming paper at ICLR 2023 on a new feature attribution method for explaining representations learned by unsupervised models!
arxiv.org/abs/2210.00107
This was joint work with the fantastic <a href="/HughChen18/">Hugh Chen</a> <a href="/ChanwooKim_/">Chanwoo Kim</a> and my advisor <a href="/suinleelab/">Su-In Lee</a>. (1/n)
Soham Gadgil (@soham_gadgil) 's Twitter Profile Photo

How to perform dynamic feature selection without assumptions about the data distribution or fitting generative models? We develop a learning approach to estimate the conditional mutual information in a discriminative fashion for selecting features. arxiv.org/pdf/2306.03301…

How to perform dynamic feature selection without assumptions about the data distribution or fitting generative models? We develop a learning approach to estimate the conditional mutual information in a discriminative fashion for selecting features. arxiv.org/pdf/2306.03301…
James Zou (@james_y_zou) 's Twitter Profile Photo

Very excited to introduce locality alignment, an efficient post-training algorithm to improve your ViTs + VLMs, essentially for free🚀 Local align = new self-supervised objective ensuring that encoder captures fine-grained spatial info. No new data needed. Here's the idea 1/3

Very excited to introduce locality alignment, an efficient post-training algorithm to improve your ViTs + VLMs, essentially for free🚀

Local align = new self-supervised objective ensuring that encoder captures fine-grained spatial info. No new data needed. Here's the idea 1/3
Sahil Verma (@sahil1v) 's Twitter Profile Photo

📣 📣 📣 Our new paper investigates the question of how many images 🖼️ of a concept are required by a diffusion model 🤖 to imitate it. This question is critical for understanding and mitigating the copyright and privacy infringements of these models! arxiv.org/abs/2410.15002

📣 📣 📣 Our new paper investigates the question of how many images 🖼️ of a concept are required by a diffusion model 🤖 to imitate it. This question is critical for understanding and mitigating the copyright and privacy infringements of these models! arxiv.org/abs/2410.15002