SE(3) Equivariant Augmented Coupling Flows

20 August 2023

Laurence I. Midgley

Vincent Stimper

Javier Antorán

Emile Mathieu

Bernhard Schölkopf

José Miguel Hernández-Lobato

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Papers citing "SE(3) Equivariant Augmented Coupling Flows"

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Title
Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching Aaron J. Havens Benjamin Kurt Miller Bing Yan Carles Domingo-Enrich Anuroop Sriram ... Brandon Amos Brian Karrer Xiang Fu Guan-Horng Liu Ricky T. Q. Chen DiffM 43 0 0 16 Apr 2025
Probabilistic Quantum SVM Training on Ising Machine Haoqi He Yan Xiao 50 0 0 20 Mar 2025
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
Training Neural Samplers with Reverse Diffusive KL Divergence Jiajun He Wenlin Chen Mingtian Zhang David Barber José Miguel Hernández-Lobato DiffM 26 4 0 16 Oct 2024
Generative Modeling of Molecular Dynamics Trajectories Bowen Jing Hannes Stärk Tommi Jaakkola Bonnie Berger AI4CE 19 3 0 26 Sep 2024
On the design space between molecular mechanics and machine learning force fields Yuanqing Wang Kenichiro Takaba Michael S. Chen Marcus Wieder Yuzhi Xu ... Kyunghyun Cho Joe G. Greener Peter K. Eastman Stefano Martiniani M. Tuckerman AI4CE 26 4 0 03 Sep 2024
Transferable Boltzmann Generators Leon Klein Frank Noé 22 11 0 20 Jun 2024
Neural Approximate Mirror Maps for Constrained Diffusion Models Berthy T. Feng Ricardo Baptista Katherine L. Bouman MedIm DiffM 30 3 0 18 Jun 2024
Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling Denis Blessing Xiaogang Jia Johannes Esslinger Francisco Vargas Gerhard Neumann 39 15 0 11 Jun 2024
Verlet Flows: Exact-Likelihood Integrators for Flow-Based Generative Models Ezra Erives Bowen Jing Tommi Jaakkola 18 1 0 05 May 2024
Fast and Unified Path Gradient Estimators for Normalizing Flows Lorenz Vaitl Ludwig Winkler Lorenz Richter Pan Kessel 13 3 0 23 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 29 20 0 01 Mar 2024
Iterated Denoising Energy Matching for Sampling from Boltzmann Densities Tara Akhound-Sadegh Jarrid Rector-Brooks A. Bose Sarthak Mittal Pablo Lemos ... Siamak Ravanbakhsh Gauthier Gidel Yoshua Bengio Nikolay Malkin Alexander Tong DiffM 27 41 0 09 Feb 2024
Conditional Normalizing Flows for Active Learning of Coarse-Grained Molecular Representations Henrik Schopmans Pascal Friederich AI4CE 13 1 0 02 Feb 2024
SE(3)-Stochastic Flow Matching for Protein Backbone Generation A. Bose Tara Akhound-Sadegh Guillaume Huguet Kilian Fatras Jarrid Rector-Brooks Cheng-Hao Liu A. Nica Maksym Korablyov Michael M. Bronstein Alexander Tong DiffM 22 71 0 03 Oct 2023
Equivariant flow matching Leon Klein Andreas Krämer Frank Noé 11 58 0 26 Jun 2023
Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics Leon Klein Andrew Y. K. Foong T. E. Fjelde Bruno Mlodozeniec Marc Brockschmidt Sebastian Nowozin Frank Noé Ryota Tomioka AI4CE 14 41 0 02 Feb 2023
Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs Yi-Lun Liao Tess E. Smidt 73 142 0 23 Jun 2022
Equivariant Finite Normalizing Flows A. Bose Marcus A. Brubaker I. Kobyzev DRL 13 8 0 16 Oct 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 183 1,218 0 08 Jan 2021