e3nn: Euclidean Neural Networks

18 July 2022

Papers citing "e3nn: Euclidean Neural Networks"

46 / 96 papers shown

Title
Lie Neurons: Adjoint-Equivariant Neural Networks for Semisimple Lie Algebras Tzu-Yuan Lin Minghan Zhu Maani Ghaffari 35 1 0 06 Oct 2023
Discovering Symmetry Breaking in Physical Systems with Relaxed Group Convolution Rui Wang E. Hofgard Han Gao Robin Walters Tess E. Smidt AI4CE 30 9 0 03 Oct 2023
HydraScreen: A Generalizable Structure-Based Deep Learning Approach to Drug Discovery Alvaro Prat Hisham Abdel-Aty Gintautas Kamuntavicius Tanya Paquet P. Norvaisas Piero Gasparotto Roy Tal 18 2 0 22 Sep 2023
Uncovering Neural Scaling Laws in Molecular Representation Learning Dingshuo Chen Yanqiao Zhu Jieyu Zhang Yuanqi Du Zhixun Li Qiang Liu Shu Wu Liang Wang 26 15 0 15 Sep 2023
Diffusion-EDFs: Bi-equivariant Denoising Generative Modeling on SE(3) for Visual Robotic Manipulation Hyunwoo Ryu Jiwoo Kim Hyun Seok Ahn Junwoo Chang Joohwan Seo Taehan Kim Yubin Kim Chaewon Hwang Jongeun Choi R. Horowitz DiffM 21 33 0 06 Sep 2023
Approximately Equivariant Graph Networks Ningyuan Huang Ron Levie Soledad Villar 32 18 0 21 Aug 2023
SE(3) Equivariant Augmented Coupling Flows Laurence I. Midgley Vincent Stimper Javier Antorán Emile Mathieu Bernhard Schölkopf José Miguel Hernández-Lobato 30 22 0 20 Aug 2023
Variational Monte Carlo on a Budget -- Fine-tuning pre-trained Neural Wavefunctions Michael Scherbela Leon Gerard Philipp Grohs 28 5 0 15 Jul 2023
Geometric Neural Diffusion Processes Emile Mathieu Vincent Dutordoir M. Hutchinson Valentin De Bortoli Yee Whye Teh Richard E. Turner DiffM 32 8 0 11 Jul 2023
MoleCLUEs: Molecular Conformers Maximally In-Distribution for Predictive Models Michael R. Maser Natasa Tagasovska Jae Hyeon Lee Andrew Watkins 31 0 0 20 Jun 2023
Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials Shengchao Liu Weitao Du Yanjing Li Zhuoxinran Li Zhiling Zheng ... Anima Anandkumar C. Borgs J. Chayes Hongyu Guo Jian Tang AI4CE 31 19 0 15 Jun 2023
M $^2$ Hub: Unlocking the Potential of Machine Learning for Materials Discovery Yuanqi Du Yingheng Wang Yin-Hua Huang Jianan Canal Li Yanqiao Zhu T. Xie Chenru Duan J. Gregoire Carla P. Gomes 32 6 0 14 Jun 2023
3D molecule generation by denoising voxel grids Pedro H. O. Pinheiro Joshua Rackers J. Kleinhenz Michael R. Maser Omar Mahmood Andrew Watkins Stephen Ra Vishnu Sresht Saeed Saremi DiffM 34 20 0 13 Jun 2023
Is novelty predictable? Clara Fannjiang Jennifer Listgarten AI4CE 17 14 0 01 Jun 2023
A General Framework for Equivariant Neural Networks on Reductive Lie Groups Ilyes Batatia Mario Geiger José M. Muñoz Tess E. Smidt L. Silberman Christoph Ortner AI4CE 27 11 0 31 May 2023
Group Invariant Global Pooling Kamil Bujel Yonatan Gideoni Chaitanya K. Joshi Pietro Lio' 37 0 0 30 May 2023
Learning Lagrangian Fluid Mechanics with E( $3$ )-Equivariant Graph Neural Networks Artur P. Toshev Gianluca Galletti Johannes Brandstetter Stefan Adami Nikolaus A. Adams AI4CE 22 5 0 24 May 2023
Evaluation of the MACE Force Field Architecture: from Medicinal Chemistry to Materials Science D. P. Kovács Ilyes Batatia E. Arany Gábor Csányi AI4CE 19 81 0 23 May 2023
KineticNet: Deep learning a transferable kinetic energy functional for orbital-free density functional theory Roman Remme Tobias Kaczun Maximilian Scheurer A. Dreuw Fred Hamprecht 20 9 0 08 May 2023
Equivariant Neural Networks for Spin Dynamics Simulations of Itinerant Magnets Y. Miyazaki 6 4 0 05 May 2023
Scaling the leading accuracy of deep equivariant models to biomolecular simulations of realistic size Albert Musaelian A. Johansson Simon L. Batzner Boris Kozinsky 22 48 0 20 Apr 2023
EigenFold: Generative Protein Structure Prediction with Diffusion Models Bowen Jing Ezra Erives Peter Pao-Huang Gabriele Corso Bonnie Berger Tommi Jaakkola DiffM 20 66 0 05 Apr 2023
Leveraging SO(3)-steerable convolutions for pose-robust semantic segmentation in 3D medical data I. Díaz Mario Geiger Richard McKinley 3DPC 11 0 0 01 Mar 2023
CHGNet: Pretrained universal neural network potential for charge-informed atomistic modeling B. Deng Peichen Zhong KyuJung Jun Janosh Riebesell K. Han Christopher J. Bartel Gerbrand Ceder 12 24 0 28 Feb 2023
Aligned Diffusion Schrödinger Bridges Vignesh Ram Somnath Matteo Pariset Ya-Ping Hsieh María Rodríguez Martínez Andreas Krause Charlotte Bunne DiffM 100 30 0 22 Feb 2023
SE(3) symmetry lets graph neural networks learn arterial velocity estimation from small datasets Julian Suk Christoph Brune J. Wolterink 25 10 0 17 Feb 2023
Fast evaluation of spherical harmonics with sphericart Filippo Bigi Guillaume Fraux N. Browning Michele Ceriotti 16 8 0 16 Feb 2023
Geometric Clifford Algebra Networks David Ruhe Jayesh K. Gupta Steven De Keninck Max Welling Johannes Brandstetter AI4CE 18 32 0 13 Feb 2023
Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs Saro Passaro C. L. Zitnick 3DPC 18 78 0 07 Feb 2023
Towards fully covariant machine learning Soledad Villar D. Hogg Weichi Yao George A. Kevrekidis Bernhard Schölkopf AI4CE 30 10 0 31 Jan 2023
Equivariant Differentially Private Deep Learning: Why DP-SGD Needs Sparser Models Florian A. Hölzl Daniel Rueckert Georgios Kaissis 16 4 0 30 Jan 2023
On the Expressive Power of Geometric Graph Neural Networks Chaitanya K. Joshi Cristian Bodnar Simon V. Mathis Taco Cohen Pietro Liò 50 83 0 23 Jan 2023
Lorentz group equivariant autoencoders Zichun Hao Raghav Kansal Javier Mauricio Duarte N. Chernyavskaya BDL DRL AI4CE 10 23 0 14 Dec 2022
Theory for Equivariant Quantum Neural Networks Quynh T. Nguyen Louis Schatzki Paolo Braccia Michael Ragone Patrick J. Coles F. Sauvage Martín Larocca M. Cerezo 27 88 0 16 Oct 2022
Hierarchical Learning in Euclidean Neural Networks Joshua A. Rackers P. Rao 28 1 0 10 Oct 2022
DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking Gabriele Corso Hannes Stärk Bowen Jing Regina Barzilay Tommi Jaakkola DiffM 130 408 0 04 Oct 2022
Holographic-(V)AE: an end-to-end SO(3)-Equivariant (Variational) Autoencoder in Fourier Space Gian Marco Visani Michael N. Pun Arman Angaji Armita Nourmohammad BDL 19 3 0 30 Sep 2022
Machine learning and invariant theory Ben Blum-Smith Soledad Villar AI4CE 31 15 0 29 Sep 2022
In Search of Projectively Equivariant Networks Georg Bökman Axel Flinth Fredrik Kahl 29 0 0 29 Sep 2022
Periodic Graph Transformers for Crystal Material Property Prediction Keqiang Yan Yi Liu Yu-Ching Lin Shuiwang Ji AI4TS 88 84 0 23 Sep 2022
Clifford Neural Layers for PDE Modeling Johannes Brandstetter Rianne van den Berg Max Welling Jayesh K. Gupta AI4CE 60 79 0 08 Sep 2022
Ab-initio quantum chemistry with neural-network wavefunctions J. Hermann J. Spencer Kenny Choo Antonio Mezzacapo W. Foulkes David Pfau Giuseppe Carleo Frank Noé AI4CE 23 73 0 26 Aug 2022
Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching Shengchao Liu Hongyu Guo Jian Tang 18 77 0 27 Jun 2022
Integrating Symmetry into Differentiable Planning with Steerable Convolutions Linfeng Zhao Xu Zhu Lingzhi Kong Robin G. Walters Lawson L. S. Wong 20 8 0 08 Jun 2022
A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups Marc Finzi Max Welling A. Wilson 71 185 0 19 Apr 2021
E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials Simon L. Batzner Albert Musaelian Lixin Sun Mario Geiger J. Mailoa M. Kornbluth N. Molinari Tess E. Smidt Boris Kozinsky 192 1,232 0 08 Jan 2021