Danqil77
@danqil7.bsky.social
CS Ph.D. @ Krishnaswamy Lab, Yale. 18' CS @ Northwestern. 20' SWE @ Meta. 22' CS @ Princeton.
excited! 🤩
The 8th annual Graph Signal Processing Workshop is back this May 14-16! Held in Montreal, CA, at MILA! GSP covers all things graphs, signals, learning, & applications!
🔗: gspworkshop.org
👉🏻Abstract submission opens Feb 1
👉🏻 Registration opens Mar 20
🔗: gspworkshop.org
👉🏻Abstract submission opens Feb 1
👉🏻 Registration opens Mar 20
Graph Signal Processing Workshop
GSP Workshop 2025.
gspworkshop.org
January 26, 2025 at 5:23 PM
excited! 🤩
Reposted by Danqil77
We are at @jointmath.bsky.social Jan 8-11!
1/8: My talk at Topological Machine Learning I
1/8: Dhananjay Bhaskar at Contributed Paper session on Topology
1/11 join our special session on Mathematical and Computational Oncology
Also check out @pseudomanifold.topology.rocks on 1/9!!
1/8: My talk at Topological Machine Learning I
1/8: Dhananjay Bhaskar at Contributed Paper session on Topology
1/11 join our special session on Mathematical and Computational Oncology
Also check out @pseudomanifold.topology.rocks on 1/9!!
January 8, 2025 at 4:41 AM
We are at @jointmath.bsky.social Jan 8-11!
1/8: My talk at Topological Machine Learning I
1/8: Dhananjay Bhaskar at Contributed Paper session on Topology
1/11 join our special session on Mathematical and Computational Oncology
Also check out @pseudomanifold.topology.rocks on 1/9!!
1/8: My talk at Topological Machine Learning I
1/8: Dhananjay Bhaskar at Contributed Paper session on Topology
1/11 join our special session on Mathematical and Computational Oncology
Also check out @pseudomanifold.topology.rocks on 1/9!!
Reposted by Danqil77
Reposted by Danqil77
Optimal transport computes an interpolation between two distributions using an optimal coupling. Flow matching, on the other hand, uses a simpler “independent” coupling, which is the product of the marginals.
December 2, 2024 at 12:46 PM
Optimal transport computes an interpolation between two distributions using an optimal coupling. Flow matching, on the other hand, uses a simpler “independent” coupling, which is the product of the marginals.
Reposted by Danqil77
✨EXCITING NEWS! We now have a Bluesky account!!
AND registration for the 3rd Learning on Graphs conference is open 😊
It is virtual, free to attend, livestreamed, and recorded 📹 Sign up today! The conference is this coming week 😱
forms.gle/eYiDCopJGUc8...
AND registration for the 3rd Learning on Graphs conference is open 😊
It is virtual, free to attend, livestreamed, and recorded 📹 Sign up today! The conference is this coming week 😱
forms.gle/eYiDCopJGUc8...
November 24, 2024 at 5:00 PM
✨EXCITING NEWS! We now have a Bluesky account!!
AND registration for the 3rd Learning on Graphs conference is open 😊
It is virtual, free to attend, livestreamed, and recorded 📹 Sign up today! The conference is this coming week 😱
forms.gle/eYiDCopJGUc8...
AND registration for the 3rd Learning on Graphs conference is open 😊
It is virtual, free to attend, livestreamed, and recorded 📹 Sign up today! The conference is this coming week 😱
forms.gle/eYiDCopJGUc8...
Reposted by Danqil77
If you're in Montreal tomorrow, catch us at the @logconference.bsky.social meetup @Mila_Quebec !
sites.google.com/view/log-202...
sites.google.com/view/log-202...
LoG 2024 Montreal
About
sites.google.com
November 25, 2024 at 2:45 AM
If you're in Montreal tomorrow, catch us at the @logconference.bsky.social meetup @Mila_Quebec !
sites.google.com/view/log-202...
sites.google.com/view/log-202...
Reposted by Danqil77
(1/n) Intro...We work on mathematical machine learning and deep learning methods that use dynamics modeling, signal processing, geometry and topology to accelerate scientific discovery from data. Our key focus is representation learning of complex unlabelled data, a host of downstream tasks:
November 21, 2024 at 1:27 PM
(1/n) Intro...We work on mathematical machine learning and deep learning methods that use dynamics modeling, signal processing, geometry and topology to accelerate scientific discovery from data. Our key focus is representation learning of complex unlabelled data, a host of downstream tasks: