Cormorant: Covariant Molecular Neural Networks

6 June 2019

Papers citing "Cormorant: Covariant Molecular Neural Networks"

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Title
Representing spherical tensors with scalar-based machine-learning models Michelangelo Domina Filippo Bigi Paolo Pegolo Michele Ceriotti 45 0 0 08 May 2025
Optimizing Data Distribution and Kernel Performance for Efficient Training of Chemistry Foundation Models: A Case Study with MACE J. Firoz Franco Pellegrini Mario Geiger Darren J. Hsu Jenna A. Bilbrey ... Chris Mundy Gábor Csányi Justin S. Smith Ponnuswamy Sadayappan Sutanay Choudhury 26 0 0 14 Apr 2025
Position: Beyond Euclidean -- Foundation Models Should Embrace Non-Euclidean Geometries Neil He Jiahong Liu Buze Zhang N. Bui Ali Maatouk Menglin Yang Irwin King Melanie Weber Rex Ying 29 0 0 11 Apr 2025
Enhancing the Scalability and Applicability of Kohn-Sham Hamiltonians for Molecular Systems Yunyang Li Zaishuo Xia Lin Huang Xinran Wei Han Yang ... Zun Wang Chang-Shu Liu Jia Zhang Bin Shao Mark B. Gerstein 77 0 0 26 Feb 2025
LMDM:Latent Molecular Diffusion Model For 3D Molecule Generation Xiang Chen DiffM 74 0 0 05 Dec 2024
TESGNN: Temporal Equivariant Scene Graph Neural Networks for Efficient and Robust Multi-View 3D Scene Understanding Quang P.M. Pham Khoi T.N. Nguyen Lan C. Ngo Dezhen Song Truong Do Truong Son-Hy 3DPC 34 2 0 15 Nov 2024
Equivariant Graph Network Approximations of High-Degree Polynomials for Force Field Prediction Zhao Xu Haiyang Yu Montgomery Bohde Shuiwang Ji 40 0 0 06 Nov 2024
Conditional Synthesis of 3D Molecules with Time Correction Sampler Hojung Jung Youngrok Park Laura Schmid Jaehyeong Jo Dongkyu Lee Bongsang Kim Se-Young Yun Jinwoo Shin DiffM 29 4 0 01 Nov 2024
ET-Flow: Equivariant Flow-Matching for Molecular Conformer Generation Majdi Hassan Nikhil Shenoy Jungyoon Lee Hannes Stärk Stephan Thaler Dominique Beaini 29 6 0 29 Oct 2024
UniGEM: A Unified Approach to Generation and Property Prediction for Molecules Shikun Feng Yuyan Ni Yan Lu Zhi-Ming Ma Wei-Ying Ma Yanyan Lan 38 5 0 14 Oct 2024
Revisiting Multi-Permutation Equivariance through the Lens of Irreducible Representations Yonatan Sverdlov Ido Springer Nadav Dym 35 2 0 09 Oct 2024
Geometric Representation Condition Improves Equivariant Molecule Generation Zian Li Cai Zhou Xiyuan Wang Xingang Peng Muhan Zhang 45 1 0 04 Oct 2024
Improved Image Classification with Manifold Neural Networks Caio F. Deberaldini Netto Zhiyang Wang Luana Ruiz AI4CE 25 0 0 19 Sep 2024
Symmetry-Based Structured Matrices for Efficient Approximately Equivariant Networks Ashwin Samudre Mircea Petrache Brian D. Nord Shubhendu Trivedi 44 2 0 18 Sep 2024
Adaptive Sampling for Continuous Group Equivariant Neural Networks Berfin Inal Gabriele Cesa 35 0 0 13 Sep 2024
Point Neuron Learning: A New Physics-Informed Neural Network Architecture Hanwen Bi T. Abhayapala PINN 21 3 0 30 Aug 2024
Cross-Modal Learning for Chemistry Property Prediction: Large Language Models Meet Graph Machine Learning Sakhinana Sagar Srinivas Venkataramana Runkana AI4CE 35 1 0 27 Aug 2024
Geometry Informed Tokenization of Molecules for Language Model Generation Xiner Li Limei Wang Youzhi Luo Carl N. Edwards Shurui Gui Yuchao Lin Heng Ji Shuiwang Ji 29 6 0 19 Aug 2024
Sampling Foundational Transformer: A Theoretical Perspective Viet Anh Nguyen Minh Lenhat Khoa Nguyen Duong Duc Hieu Dao Huu Hung Truong Son-Hy 44 0 0 11 Aug 2024
Scalable learning of potentials to predict time-dependent Hartree-Fock dynamics Harish S. Bhat Prachi Gupta Christine M Isborn 30 1 0 08 Aug 2024
On the Expressive Power of Sparse Geometric MPNNs Yonatan Sverdlov Nadav Dym 42 1 0 02 Jul 2024
GeoMFormer: A General Architecture for Geometric Molecular Representation Learning Tianlang Chen Shengjie Luo Di He Shuxin Zheng Tie-Yan Liu Liwei Wang AI4CE 38 5 0 24 Jun 2024
Molecule Graph Networks with Many-body Equivariant Interactions Zetian Mao Jiawen Li Chen Liang Diptesh Das Masato Sumita Koji Tsuda Kelin Xia Koji Tsuda 35 1 0 19 Jun 2024
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency Yuchao Lin Jacob Helwig Shurui Gui Shuiwang Ji 39 7 0 11 Jun 2024
Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models Zun Wang Chang-Shu Liu Nianlong Zou He Zhang Xinran Wei Lin Huang Lijun Wu Bin Shao 36 1 0 06 Jun 2024
Neural Polarization: Toward Electron Density for Molecules by Extending Equivariant Networks Bumju Kwak Jeonghee Jo 47 0 0 01 Jun 2024
A Recipe for Charge Density Prediction Xiang Fu Andrew S. Rosen Kyle Bystrom Rui Wang Albert Musaelian Boris Kozinsky Tess E. Smidt Tommi Jaakkola 50 5 0 29 May 2024
SE3Set: Harnessing equivariant hypergraph neural networks for molecular representation learning Hongfei Wu Lijun Wu Guoqing Liu Zhirong Liu Bin Shao Zun Wang 40 1 0 26 May 2024
E(n) Equivariant Topological Neural Networks Claudio Battiloro Ege Karaismailoglu Mauricio Tec George Dasoulas Michelle Audirac Francesca Dominici 52 5 0 24 May 2024
Steerable Transformers Soumyabrata Kundu Risi Kondor ViT LLMSV 30 1 0 24 May 2024
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing Viktor Zaverkin Francesco Alesiani Takashi Maruyama Federico Errica Henrik Christiansen Makoto Takamoto Nicolas Weber Mathias Niepert 46 5 0 23 May 2024
HEroBM: a deep equivariant graph neural network for universal backmapping from coarse-grained to all-atom representations Daniele Angioletti S. Raniolo V. Limongelli 21 0 0 25 Apr 2024
RiEMann: Near Real-Time SE(3)-Equivariant Robot Manipulation without Point Cloud Segmentation Chongkai Gao Zhengrong Xue Shuying Deng Tianhai Liang Siqi Yang Lin Shao Huazhe Xu 3DPC 36 10 0 28 Mar 2024
Unified Generative Modeling of 3D Molecules via Bayesian Flow Networks Yuxuan Song Jingjing Gong Yanru Qu Hao Zhou Mingyue Zheng Jingjing Liu Wei-Ying Ma 33 10 0 17 Mar 2024
An intuitive multi-frequency feature representation for SO(3)-equivariant networks Dongwon Son Jaehyung Kim Sanghyeon Son Beomjoon Kim 3DPC 38 1 0 15 Mar 2024
A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications Jiaqi Han Jiacheng Cen Liming Wu Zongzhao Li Xiangzhe Kong ... Zhewei Wei Deli Zhao Yu Rong Wenbing Huang Wenbing Huang AI4CE 34 20 0 01 Mar 2024
TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations Raúl P. Peláez Guillem Simeon Raimondas Galvelis Antonio Mirarchi Peter K. Eastman Stefan Doerr Philipp Thölke T. Markland Gianni de Fabritiis AI4CE 30 12 0 27 Feb 2024
Pretraining Strategy for Neural Potentials Zehua Zhang Zijie Li A. Farimani AI4CE 42 0 0 24 Feb 2024
D-Flow: Differentiating through Flows for Controlled Generation Heli Ben-Hamu Omri Puny Itai Gat Brian Karrer Uriel Singer Y. Lipman 41 24 0 21 Feb 2024
Cartesian atomic cluster expansion for machine learning interatomic potentials Bingqing Cheng 34 31 0 12 Feb 2024
E(3)-Equivariant Mesh Neural Networks Thuan Trang Nhat-Khang Ngô Daniel Levy Thieu N. Vo Siamak Ravanbakhsh Truong Son-Hy MDE 39 3 0 07 Feb 2024
Triplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph Transformers Md Shamim Hussain Mohammed J. Zaki D. Subramanian ViT 28 5 0 07 Feb 2024
Energy-conserving equivariant GNN for elasticity of lattice architected metamaterials I. Grega Ilyes Batatia Gábor Csányi Sri Karlapati Vikram S. Deshpande 19 3 0 30 Jan 2024
Equivariant Flow Matching with Hybrid Probability Transport Yuxuan Song Jingjing Gong Minkai Xu Ziyao Cao Yanyan Lan Stefano Ermon Hao Zhou Wei-Ying Ma DiffM 28 45 0 12 Dec 2023
Expressive Sign Equivariant Networks for Spectral Geometric Learning Derek Lim Joshua Robinson Stefanie Jegelka Haggai Maron 71 16 0 04 Dec 2023
$Learning Polynomial Problems with $SL(2,\mathbb{R})$ Equivariance$ Learning Polynomial Problems with $SL(2,\mathbb{R})$ Equivariance Hannah Lawrence Mitchell Tong Harris 27 1 0 04 Dec 2023
A Universal Framework for Accurate and Efficient Geometric Deep Learning of Molecular Systems Shuo-feng Zhang Yang Liu Lei Xie AI4CE GNN PINN 29 10 0 19 Nov 2023
ShapeMatcher: Self-Supervised Joint Shape Canonicalization, Segmentation, Retrieval and Deformation Yan Di Chenyangguang Zhang Chaowei Wang Ruida Zhang Guangyao Zhai Yanyan Li Bowen Fu Xiangyang Ji Shan Gao 3DPC 21 5 0 18 Nov 2023
Sample Complexity Bounds for Estimating Probability Divergences under Invariances B. Tahmasebi Stefanie Jegelka 49 6 0 06 Nov 2023
Accelerating Electronic Stopping Power Predictions by 10 Million Times with a Combination of Time-Dependent Density Functional Theory and Machine Learning Logan T. Ward B. Blaiszik Cheng-Wei Lee Troy Martin Ian T. Foster A. Schleife 11 4 0 01 Nov 2023