Victor Garcia Satorras | DeepAI

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∙ 02/01/2023

Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamics

Coarse-grained (CG) molecular dynamics enables the study of biological p...

0 Marloes Arts, et al. ∙

∙ 10/11/2022

Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design

Fragment-based drug discovery has been an effective paradigm in early-st...

5 Ilia Igashov, et al. ∙

∙ 03/31/2022

Equivariant Diffusion for Molecule Generation in 3D

This work introduces a diffusion model for molecule generation in 3D tha...

0 Emiel Hoogeboom, et al. ∙

∙ 03/07/2022

Multivariate Time Series Forecasting with Latent Graph Inference

This paper introduces a new approach for Multivariate Time Series foreca...

0 Victor Garcia Satorras, et al. ∙

∙ 09/10/2021

A Study of Joint Graph Inference and Forecasting

We study a recent class of models which uses graph neural networks (GNNs...

0 Daniel Zügner, et al. ∙

∙ 05/19/2021

E(n) Equivariant Normalizing Flows for Molecule Generation in 3D

This paper introduces a generative model equivariant to Euclidean symmet...

14 Victor Garcia Satorras, et al. ∙

∙ 02/19/2021

E(n) Equivariant Graph Neural Networks

This paper introduces a new model to learn graph neural networks equivar...

0 Victor Garcia Satorras, et al. ∙

∙ 06/02/2020

The Convolution Exponential and Generalized Sylvester Flows

This paper introduces a new method to build linear flows, by taking the ...

10 Emiel Hoogeboom, et al. ∙

∙ 03/04/2020

Neural Enhanced Belief Propagation on Factor Graphs

A graphical model is a structured representation of locally dependent ra...

16 Victor Garcia Satorras, et al. ∙

∙ 06/06/2019

Combining Generative and Discriminative Models for Hybrid Inference

A graphical model is a structured representation of the data generating ...

8 Victor Garcia Satorras, et al. ∙

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