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Andrei Manolache

@amanolache

ELLIS PhD Student @ IMPRS-IS/Uni Stuttgart; ML Research @ Bitdefender | https://andreimano.github.io/

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12.11.2024
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Latest posts by Andrei Manolache @amanolache

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EEML'25, our yearly machine learning summer school event, will be organised next summer in the beautiful city of Sarajevo - the place where East meets West πŸ‡§πŸ‡¦πŸ‡§πŸ‡¦πŸ‡§πŸ‡¦.

More details coming soon, please see the link in the thread!

15.12.2024 18:22 πŸ‘ 18 πŸ” 6 πŸ’¬ 1 πŸ“Œ 1
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Catch my poster tomorrow at the NeurIPS MLSB Workshop! We present a simple (yet effective 😁) multimodal Transformer for molecules, supporting multiple 3D conformations & showing promise for transfer learning.

Interested in molecular representation learning? Let’s chat πŸ‘‹!

15.12.2024 00:31 πŸ‘ 10 πŸ” 2 πŸ’¬ 0 πŸ“Œ 0

* in the afternoon session πŸ˜…

11.12.2024 22:27 πŸ‘ 0 πŸ” 0 πŸ’¬ 0 πŸ“Œ 0

Happening today, East Exhibit Hall A-C, poster #3110. Come say "Hi!"! πŸ‘‹

11.12.2024 18:21 πŸ‘ 1 πŸ” 0 πŸ’¬ 1 πŸ“Œ 0

6/6 Interested in learning more? Check out our preprint here: arxiv.org/pdf/2405.17311.
If you’d like to discuss, I’d be very happy to chat during the poster session in Vancouver! :)

07.12.2024 17:52 πŸ‘ 1 πŸ” 0 πŸ’¬ 2 πŸ“Œ 0
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5/6 How it works: Probabilistic sampling connects original nodes to virtual ones, enhancing connectivity without explicit pairwise computations. The result is a framework that achieves both higher WL expressiveness and efficiency in graph-based learning.

07.12.2024 17:52 πŸ‘ 0 πŸ” 0 πŸ’¬ 1 πŸ“Œ 0
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4/6 We demonstrate SOTA results on various benchmarks, effectively addressing over-squashing and under-reaching. IPR-MPNNs also surpass standard MPNNs in expressiveness, distinguishing complex graph structuresβ€”all while being faster and more memory-efficient than GTs. πŸš€

07.12.2024 17:51 πŸ‘ 0 πŸ” 0 πŸ’¬ 1 πŸ“Œ 0
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3/6 Enter IPR-MPNNs: Our approach learns to rewire graphs probabilistically by adding virtual nodes. This eliminates the need for heuristics, making the method more flexible and task-adaptive, while maintaining computational efficiency. 🎯

07.12.2024 17:51 πŸ‘ 1 πŸ” 0 πŸ’¬ 1 πŸ“Œ 0

2/6 Standard MPNNs struggle with long-range interactions, making them less effective for large, complex graphs. Transformers help but come with quadratic complexity, which is computationally expensive. Rewiring heuristics? Often brittle and task-specific.

07.12.2024 17:50 πŸ‘ 0 πŸ” 0 πŸ’¬ 1 πŸ“Œ 0
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1/6 We're excited to share our #NeurIPS2024 paper: Probabilistic Graph Rewiring via Virtual Nodes! It addresses key challenges in GNNs, such as over-squashing and under-reaching, while reducing reliance on heuristic rewiring. w/ Chendi Qian, @christophermorris.bsky.social @mniepert.bsky.social 🧡

07.12.2024 17:50 πŸ‘ 30 πŸ” 6 πŸ’¬ 1 πŸ“Œ 0

Genuine question - why do captions go above tables? I've always assumed that this is due to wanting to make tables distinct from figures, but it seems like a convention.

29.11.2024 01:20 πŸ‘ 2 πŸ” 0 πŸ’¬ 1 πŸ“Œ 1

πŸ‘€πŸ‘‹

18.11.2024 15:35 πŸ‘ 1 πŸ” 0 πŸ’¬ 1 πŸ“Œ 0