:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Alesiani, Francesco, Warrell, Jonathan, Bien, Tanja, Christiansen, Henrik, Ferraz, Matheus, Niepert, Mathias
Format:	Preprint
Publié:	2026
Sujets:	Machine Learning
Accès en ligne:	https://arxiv.org/abs/2602.05549
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations
par: Zaverkin, Viktor, et autres
Publié: (2025)

Adaptive Width Neural Networks
par: Errica, Federico, et autres
Publié: (2025)

Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching
par: Errica, Federico, et autres
Publié: (2023)

Variational Kolmogorov-Arnold Network
par: Alesiani, Francesco, et autres
Publié: (2025)

Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing
par: Zaverkin, Viktor, et autres
Publié: (2024)

Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials
par: Zaverkin, Viktor, et autres
Publié: (2023)

Self-Tuning Hamiltonian Monte Carlo for Accelerated Sampling
par: Christiansen, Henrik, et autres
Publié: (2023)

Geometric Kolmogorov-Arnold Superposition Theorem
par: Alesiani, Francesco, et autres
Publié: (2025)

SymDrift: One-Shot Generative Modeling under Symmetries
par: Darouich, Samir, et autres
Publié: (2026)

PDEBENCH: An Extensive Benchmark for Scientific Machine Learning
par: Takamoto, Makoto, et autres
Publié: (2022)

Fast, Modular, and Differentiable Framework for Machine Learning-Enhanced Molecular Simulations
par: Christiansen, Henrik, et autres
Publié: (2025)

Adaptive Physics-informed Neural Networks: A Survey
par: Torres, Edgar, et autres
Publié: (2025)

Graph Reasoning Networks
par: Zopf, Markus, et autres
Publié: (2024)

Image Inpainting via Tractable Steering of Diffusion Models
par: Liu, Anji, et autres
Publié: (2023)

Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks
par: Errica, Federico, et autres
Publié: (2023)

L2XGNN: Learning to Explain Graph Neural Networks
par: Serra, Giuseppe, et autres
Publié: (2022)

Discrete Copula Diffusion
par: Liu, Anji, et autres
Publié: (2024)

SMART: Scalable Mesh-free Aerodynamic Simulations from Raw Geometries using a Transformer-based Surrogate Model
par: Hagnberger, Jan, et autres
Publié: (2026)

Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad
par: Warrell, Jonathan, et autres
Publié: (2024)

MolMix: A Simple Yet Effective Baseline for Multimodal Molecular Representation Learning
par: Manolache, Andrei, et autres
Publié: (2024)

Learning the Neighborhood: Contrast-Free Multimodal Self-Supervised Molecular Graph Pretraining
par: Ariguib, Boshra, et autres
Publié: (2025)

Learning to Discretize Denoising Diffusion ODEs
par: Tong, Vinh, et autres
Publié: (2024)

Rao-Blackwell Gradient Estimators for Equivariant Denoising Diffusion
par: Tong, Vinh, et autres
Publié: (2025)

Probabilistic Graph Rewiring via Virtual Nodes
par: Qian, Chendi, et autres
Publié: (2024)

Adaptive Transition State Refinement with Learned Equilibrium Flows
par: Darouich, Samir, et autres
Publié: (2025)

Clifford Kolmogorov-Arnold Networks
par: Wolff, Matthias, et autres
Publié: (2026)

Physics-Informed Weakly Supervised Learning for Interatomic Potentials
par: Takamoto, Makoto, et autres
Publié: (2024)

CALM-PDE: Continuous and Adaptive Convolutions for Latent Space Modeling of Time-dependent PDEs
par: Hagnberger, Jan, et autres
Publié: (2025)

LOGLO-FNO: Efficient Learning of Local and Global Features in Fourier Neural Operators
par: Kalimuthu, Marimuthu, et autres
Publié: (2025)

What Exactly Does Guidance Do in Masked Discrete Diffusion Models
par: Ye, He, et autres
Publié: (2025)

Preference-Based Gradient Estimation for ML-Guided Approximate Combinatorial Optimization
par: Mielke, Arman, et autres
Publié: (2025)

Learning (Approximately) Equivariant Networks via Constrained Optimization
par: Manolache, Andrei, et autres
Publié: (2025)

Protein Fold Classification at Scale: Benchmarking and Pretraining
par: Chen, Dexiong, et autres
Publié: (2026)

CoInD: Enabling Logical Compositions in Diffusion Models
par: Gaudi, Sachit, et autres
Publié: (2025)

SIMPLE: A Gradient Estimator for $k$-Subset Sampling
par: Ahmed, Kareem, et autres
Publié: (2022)

Exploiting the Exact Denoising Posterior Score in Training-Free Guidance of Diffusion Models
par: Bellchambers, Gregory
Publié: (2025)

Discrete Guidance Matching: Exact Guidance for Discrete Flow Matching
par: Wan, Zhengyan, et autres
Publié: (2025)

Vectorized Conditional Neural Fields: A Framework for Solving Time-dependent Parametric Partial Differential Equations
par: Hagnberger, Jan, et autres
Publié: (2024)

Improving Discriminator Guidance in Diffusion Models
par: Verine, Alexandre, et autres
Publié: (2025)

Active Learning for Neural PDE Solvers
par: Musekamp, Daniel, et autres
Publié: (2024)