Aseem Baranwal @aseemrb
ML on graphs @UWCheritonCS, https://t.co/GwxAWCdQDQ. Prev research intern @MSFTResearch, @GoogleAI. aseemrb.me Minkowski spacetime Joined March 2010-
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Waterloo Computational Learning Lab it is: watcl.ca! I rebranded our lab after six years to better reflect the work we do and will continue to do in the future.
Presenting "Optimal Fair Learning Robust to Adversarial Distribution Shift" at #ICML2025 (openreview.net/pdf?id=TGcXwWd…) 📍East Exhibition Hall A-B #E-1001 ⏲️16th July, 4:30-7PM Please have a look, and do stop by if it sounds interesting to you! RT's appreciated😊Summary to follow
My former PhD student, Aseem Baranwal, won the PhD Dissertation Award from the Department of Computer Science at the University of Waterloo for his thesis, “Statistical Foundations for Learning on Graphs.” Aseem is the first PhD student I graduated, and I couldn't be happier for…
My former PhD student, Aseem Baranwal, won the PhD Dissertation Award from the Department of Computer Science at the University of Waterloo for his thesis, “Statistical Foundations for Learning on Graphs.” Aseem is the first PhD student I graduated, and I couldn't be happier for… https://t.co/nF0nKrPyg9
Positional Attention: Out-of-Distribution Generalization and Expressivity for Neural Algorithmic Reasoning We propose calculating the attention weights in Transformers using only fixed positional encodings (referred to as positional attention). These positional encodings remain…
This paper was just accepted at NeurIPS. I am particularly happy about this because it originated as a course project by Robert in our Graph Neural Networks course.
This paper was just accepted at NeurIPS. I am particularly happy about this because it originated as a course project by Robert in our Graph Neural Networks course.
If you are at #ICML2024 and interested in the theory of graph neural networks, come by our poster 'Graph Attention Retrospective.' conference link: icml.cc/virtual/2024/p… paper: jmlr.org/papers/v24/22-… relevant blog: medium.com/@kimon.fountou…
I guess that as of today I can also announce that I have been promoted to the rank of Associate Professor. I am mostly making this post to publicly thank all the people who have supported me during my career, especially my first two PhD students, @aseemrb and @shenghao_yang (in…
For those participating in the Complex Networks in Banking and Finance Workshop, I’ll be presenting our work on Local Graph Clustering with Noisy Labels tomorrow at 9:20 AM EDT at the Fields Institute. Hope to see you there :) arxiv.org/abs/2310.08031
Paper: Simulation of Graph Algorithms with Looped Transformers (revised version @icmlconf) + Multi-tasking (Remark 6.5) + Discussion on the role of ill-conditioning for the ability of Transformers to simulate algorithms. Link: arxiv.org/abs/2402.01107
Paper: Simulation of Graph Algorithms with Looped Transformers (revised version @icmlconf) + Multi-tasking (Remark 6.5) + Discussion on the role of ill-conditioning for the ability of Transformers to simulate algorithms. Link: arxiv.org/abs/2402.01107
Paper: Analysis of Corrected Graph Convolutions We study the performance of a vanilla graph convolution from which we remove the principal eigenvector to avoid oversmoothing. 1) We perform a spectral analysis for k rounds of corrected graph convolutions, and we provide results…
.@backdeluca is at ICLR and he will present his joint work with @shenghao_yang on "Local Graph Clustering with Noisy Labels". Date: Friday 10th of May. Time: 4:30pm - 6:30pm CEST. Place: Halle B #175.
.@backdeluca's paper got accepted at ICML. The final version will include a proof for multi-tasking and comments about training + other clarifications. I will post the updated version soon. I would like to thank the reviewers for their valuable feedback. The above extensions…
.@backdeluca's paper got accepted at ICML. The final version will include a proof for multi-tasking and comments about training + other clarifications. I will post the updated version soon. I would like to thank the reviewers for their valuable feedback. The above extensions…
If your model is weak, your paper might end up getting more citations because people are always happy to include your model as a baseline.
Paper: Simulation of Graph Algorithms with Looped Transformers Current empirical results illustrate promising scale generalization in executing classical graph algorithms. The predominant approach in these studies is to train a neural network to execute a step of a target…
Our paper was accepted at ICLR 2024. First paper of @backdeluca as a PhD student in our group!
Our paper was accepted at ICLR 2024. First paper of @backdeluca as a PhD student in our group!
Sina Baghal @s_baghal
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Djordje Zivanovic, Ph... @popina1994
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Valters Jēkabs Zakre... @Valtersjz
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Dr. Adedeji Oladimeji... @dejavuadebare
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Ed Blyden @EdBlyden
41 Followers 2K Following I'm pretty good at breathing while sleeping. Zionism = Nazism = Genocide Fuck Israel
Ritabrata Ray @ritabrataray
257 Followers 2K Following PhD student @mldcmu, previously MS @Cornell, and undergrad @IITKgp
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z @betaokumura
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Emile van Krieken @EmilevanKrieken
2K Followers 817 Following Postdoc @ VU Amsterdam, prev University of Edinburgh | Neurosymbolic Machine Learning Mostly moved to 🦋, will only post news here
Raj Gupta @the_perceptron
150 Followers 2K Following Founding Lead AI R&D || Healthcare AI Agent R&D — Hospitals & Medical Tourism (for EU and Middle East)
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Math, Inc. @mathematics_inc
6K Followers 0 Following A new company dedicated to autoformalization and the creation of verified superintelligence.
Sina Baghal @s_baghal
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MathMatize Memes @MathMatize
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The PhD Place @ThePhDPlace
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NeurIPS Conference @NeurIPSConf
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Historic Vids @historyinmemes
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Institute for Protein... @UWproteindesign
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Hank Green @hankgreen
1.5M Followers 979 Following This account is not actively managed, it sometimes reposts from my Bluesky, a Twitter-like thing that’s built on an open platform, giving its users more control
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Transactions on Machi... @TmlrOrg
6K Followers 5 Following Transactions on Machine Learning Research (TMLR) is a new venue for dissemination of machine learning research
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10K Followers 771 Following LoG is a new annual research conference that covers areas broadly related to machine learning on graphs and geometry, with a special focus on review quality.Trends for United States
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