SchNet: A continuous-filter convolutional neural network for modeling quantum interactions

26 June 2017

Kristof T. Schütt

Pieter-Jan Kindermans

Huziel Enoc Sauceda Felix

Papers citing "SchNet: A continuous-filter convolutional neural network for modeling quantum interactions"

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Title
RISE: Radius of Influence based Subgraph Extraction for 3D Molecular Graph Explanation J. Qu Wenhan Gao Jiaxing Zhang Xufeng Liu Hua Wei Haibin Ling Y. Liu AI4CE 55 0 0 04 May 2025
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Quantifying Robustness: A Benchmarking Framework for Deep Learning Forecasting in Cyber-Physical Systems Alexander Windmann Henrik S. Steude Daniel Boschmann Oliver Niggemann OOD AI4TS 33 0 0 04 Apr 2025
Force-Free Molecular Dynamics Through Autoregressive Equivariant Networks Fabian L. Thiemann Thiago Reschützegger Massimiliano Esposito Tseden Taddese Juan D. Olarte-Plata Fausto Martelli AI4CE 49 0 0 31 Mar 2025
NaFM: Pre-training a Foundation Model for Small-Molecule Natural Products Yuheng Ding Yusong Wang Bo Qiang Jie Yu Qi Li Yiran Zhou Zhenmin Liu 159 0 0 22 Mar 2025
MatterChat: A Multi-Modal LLM for Material Science Yingheng Tang Wenbin Xu Jie Cao Jianzhu Ma Weilu Gao Steve Farrell Benjamin Erichson Michael W. Mahoney Andy Nonaka 113 3 0 18 Feb 2025
Is attention all you need to solve the correlated electron problem? Max Geier Khachatur Nazaryan Timothy Zaklama Liang Fu 43 3 0 07 Feb 2025
FastCHGNet: Training one Universal Interatomic Potential to 1.5 Hours with 32 GPUs Yuanchang Zhou Siyu Hu Chen Wang Lin-Wang Wang Guangming Tan Weile Jia AI4CE GNN 50 0 0 30 Dec 2024
MOL-Mamba: Enhancing Molecular Representation with Structural & Electronic Insights Jingjing Hu D. Guo Zhan Si Deguang Liu Yunfeng Diao J. Zhang Jinxing Zhou Meng Wang Mamba 98 1 0 21 Dec 2024
Predicting ionic conductivity in solids from the machine-learned potential energy landscape Artem Maevskiy Alexandra Carvalho Emil Sataev Volha Turchyna Keian Noori Aleksandr Rodin A. H. Castro Neto Andrey E. Ustyuzhanin 37 0 0 11 Nov 2024
Neural Network Matrix Product Operator: A Multi-Dimensionally Integrable Machine Learning Potential Kentaro Hino Yuki Kurashige 34 0 0 31 Oct 2024
Beyond Sequence: Impact of Geometric Context for RNA Property Prediction Junjie Xu Artem Moskalev Tommaso Mansi Mangal Prakash Rui Liao AI4CE 26 1 0 15 Oct 2024
Learning Equivariant Non-Local Electron Density Functionals Nicholas Gao Eike Eberhard Stephan Günnemann 28 1 0 10 Oct 2024
Deep Signature: Characterization of Large-Scale Molecular Dynamics Tiexin Qin Mengxu Zhu Chunyang Li Terry Lyons Hong Yan Haoliang Li 28 0 0 03 Oct 2024
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Physics-Informed Weakly Supervised Learning for Interatomic Potentials Makoto Takamoto Viktor Zaverkin Mathias Niepert AI4CE 60 0 0 23 Jul 2024
SE(3)-Hyena Operator for Scalable Equivariant Learning Artem Moskalev Mangal Prakash Rui Liao Tommaso Mansi 46 2 0 01 Jul 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
Neural Thermodynamic Integration: Free Energies from Energy-based Diffusion Models Bálint Máté François Fleuret Tristan Bereau DiffM 40 2 0 04 Jun 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
Deep Learning Method for Computing Committor Functions with Adaptive Sampling Bo Lin Weiqing Ren 18 3 0 09 Apr 2024
Grappa -- A Machine Learned Molecular Mechanics Force Field Leif Seute Eric Hartmann Jan Stühmer Frauke Gräter 29 3 0 25 Mar 2024
Unified Static and Dynamic Network: Efficient Temporal Filtering for Video Grounding Jingjing Hu Dan Guo Kun Li Zhan Si Xun Yang Xiaojun Chang Meng Wang 59 3 0 21 Mar 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
Molecular Property Prediction Based on Graph Structure Learning Bangyi Zhao Weixia Xu Jihong Guan Shuigeng Zhou 19 7 0 28 Dec 2023
Molecular Hypergraph Neural Networks Junwu Chen Philippe Schwaller GNN 41 10 0 20 Dec 2023
Predicting Properties of Periodic Systems from Cluster Data: A Case Study of Liquid Water Viktor Zaverkin David Holzmüller Robin Schuldt Johannes Kastner 28 15 0 03 Dec 2023
Multiscale Hodge Scattering Networks for Data Analysis Naoki Saito Stefan C. Schonsheck Eugene Shvarts 32 1 0 17 Nov 2023
STRIDE: Structure-guided Generation for Inverse Design of Molecules Shehtab Zaman D. Akhiyarov Mauricio Araya-Polo Kenneth Chiu 21 1 0 06 Nov 2023
Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel Xuan Li Zhanke Zhou Jiangchao Yao Yu Rong Lu Zhang Bo Han 37 3 0 02 Nov 2023
From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction Nima Shoghi Adeesh Kolluru John R. Kitchin Zachary W. Ulissi C. L. Zitnick Brandon M. Wood AI4CE 24 32 0 25 Oct 2023
LLM-Prop: Predicting Physical And Electronic Properties Of Crystalline Solids From Their Text Descriptions Andre Niyongabo Rubungo Craig Arnold Barry P. Rand Adji Bousso Dieng AI4CE 41 28 0 21 Oct 2023
Scalable Diffusion for Materials Generation Mengjiao Yang KwangHwan Cho Amil Merchant Pieter Abbeel Dale Schuurmans Igor Mordatch E. D. Cubuk 29 39 0 18 Oct 2023
On the importance of catalyst-adsorbate 3D interactions for relaxed energy predictions Alvaro Carbonero Alexandre Duval Victor Schmidt Santiago Miret Alex Hernandez-Garcia Yoshua Bengio David Rolnick 32 0 0 10 Oct 2023
DrugCLIP: Contrastive Protein-Molecule Representation Learning for Virtual Screening Bowen Gao Bo Qiang Haichuan Tan Minsi Ren Yinjun Jia Minsi Lu Jingjing Liu Wei-Ying Ma Yanyan Lan 29 9 0 10 Oct 2023
3D-Mol: A Novel Contrastive Learning Framework for Molecular Property Prediction with 3D Information Taojie Kuang Yiming Ren Zhixiang Ren 23 7 0 28 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 32 16 0 15 Sep 2023
Beyond MD17: the reactive xxMD dataset Zihan Pengmei Junyu Liu Yinan Shu 21 6 0 22 Aug 2023
Learned Gridification for Efficient Point Cloud Processing P. A. V. D. Linden David W. Romero Erik J. Bekkers 3DPC 20 2 0 22 Jul 2023
Variational Monte Carlo on a Budget -- Fine-tuning pre-trained Neural Wavefunctions Michael Scherbela Leon Gerard Philipp Grohs 33 5 0 15 Jul 2023
Scaling Spherical CNNs Carlos Esteves Jean-Jacques E. Slotine A. Makadia GNN LRM 19 14 0 08 Jun 2023
Generalist Equivariant Transformer Towards 3D Molecular Interaction Learning Xiangzhe Kong Wen-bing Huang Yang Liu 22 13 0 02 Jun 2023
Towards Semi-supervised Universal Graph Classification Xiao Luo Yusheng Zhao Yifang Qin Wei Ju Ming Zhang 20 30 0 31 May 2023
Investigating how ReLU-networks encode symmetries Georg Bökman Fredrik Kahl 24 6 0 26 May 2023
A Score-Based Model for Learning Neural Wavefunctions Xuan Zhang Shenglong Xu Shuiwang Ji DiffM 25 1 0 25 May 2023
HybridNet: Dual-Branch Fusion of Geometrical and Topological Views for VLSI Congestion Prediction Yuxiang Zhao Zhuomin Chai Yibo Lin Runsheng Wang Ru Huang 13 4 0 07 May 2023
3D Molecular Geometry Analysis with 2D Graphs Zhao Xu Yaochen Xie Youzhi Luo Xuan Zhang Xinyi Xu Meng Liu Kaleb Dickerson Cheng Deng Maho Nakata Shuiwang Ji 19 1 0 01 May 2023
FAENet: Frame Averaging Equivariant GNN for Materials Modeling Alexandre Duval Victor Schmidt A. Garcia Santiago Miret Fragkiskos D. Malliaros Yoshua Bengio David Rolnick 29 54 0 28 Apr 2023
An Equivariant Generative Framework for Molecular Graph-Structure Co-Design Zaixin Zhang Qi Liu Cheekong Lee Chang-Yu Hsieh Enhong Chen 15 18 0 12 Apr 2023