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Multi-Type Point Cloud Autoencoder: A Complete Equivariant Embedding for
  Molecule Conformation and Pose

Multi-Type Point Cloud Autoencoder: A Complete Equivariant Embedding for Molecule Conformation and Pose

22 May 2024
Michael Kilgour
Mark Tuckerman
J. Rogal
ArXivPDFHTML

Papers citing "Multi-Type Point Cloud Autoencoder: A Complete Equivariant Embedding for Molecule Conformation and Pose"

5 / 5 papers shown
Title
Geometric Latent Diffusion Models for 3D Molecule Generation
Geometric Latent Diffusion Models for 3D Molecule Generation
Minkai Xu
Alexander Powers
R. Dror
Stefano Ermon
J. Leskovec
DiffM
AI4CE
45
131
0
02 May 2023
A data-driven interpretation of the stability of molecular crystals
A data-driven interpretation of the stability of molecular crystals
Rose K. Cersonsky
Maria Pakhnova
Edgar A. Engel
Michele Ceriotti
21
2
0
21 Sep 2022
Vector Neurons: A General Framework for SO(3)-Equivariant Networks
Vector Neurons: A General Framework for SO(3)-Equivariant Networks
Congyue Deng
Or Litany
Yueqi Duan
A. Poulenard
Andrea Tagliasacchi
Leonidas J. Guibas
3DPC
102
314
0
25 Apr 2021
Auto-Encoding Molecular Conformations
Auto-Encoding Molecular Conformations
R. Winter
Frank Noé
Djork-Arné Clevert
AI4CE
34
12
0
05 Jan 2021
PointNet: Deep Learning on Point Sets for 3D Classification and
  Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
C. Qi
Hao Su
Kaichun Mo
Leonidas J. Guibas
3DH
3DPC
3DV
PINN
219
13,886
0
02 Dec 2016
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