[ML Seminar] Extra IDA ML seminar - Mikkel N. Schmidt - Equivariant Neural Diffusion for Molecule Generation - 6/11

[Louis Ohl]

Welcome to an extra IDA Machine Learning Seminar on Thursday, November 6 at 13:30 In John Von Neumann

Speaker: Mikkel N. Schmidt<http://mikkelschmidt.dk/index.html>, Technical University of Denmark, DTU Compute

Title: Equivariant Neural Diffusion for Molecule Generation

Abstract: I present Equivariant Neural Diffusion (END) — an approach for generating 3D molecular structures that fully respects Euclidean symmetries. Unlike existing equivariant diffusion models, END introduces a learnable forward process that adapts dynamically to both time and data, while remaining equivariant to rigid transformations. This flexibility improves the generative capabilities of the model and opens up new possibilities for molecular design. Results on standard benchmarks show that END achieves competitive performance in both unconditional and conditional molecule generation tasks.

Location: John Von Neumann, https://link.mazemap.com/jPVeR5ZQ

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ADDENDUM: In relation to this seminar, we encourage you to come to Filip Ekström Kelvinius' PhD defence who will speak about "Deep Learning for the Atomic Scale: Graph Neural Networks and Deep Generative Models with Some Applications to Materials and Molecules<https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-218503>". The defence takes place on Friday 7/11 at 13.30 in Ada Lovelace. Our guest, Mikkel N. Schmidt, will be the opponent of Filip.

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Louis Ohl
Postdoc
louis.ohl at liu.se

Linköping University
IDA / STIMA
B-Huset, 2A:445
Webpage<https://oshillou.github.io/>
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