Cover Image

MSPT: Efficient Large-Scale Physical Modeling via Parallelized Multi-Scale Attention

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Curvo, Pedro M. P., van de Meent, Jan-Willem, Zhdanov, Maksim
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Follow the Mean: Reference-Guided Flow Matching
by: Curvo, Pedro M. P., et al.
Published: (2026)

Erwin: A Tree-based Hierarchical Transformer for Large-scale Physical Systems
by: Zhdanov, Maksim, et al.
Published: (2025)

(Sparse) Attention to the Details: Preserving Spectral Fidelity in ML-based Weather Forecasting Models
by: Zhdanov, Maksim, et al.
Published: (2026)

Crystalite: A Lightweight Transformer for Efficient Crystal Modeling
by: Veljković, Tin Hadži, et al.
Published: (2026)

Conditional Clifford-Steerable CNNs with Complete Kernel Basis for PDE Modeling
by: Szarvas, Bálint László, et al.
Published: (2025)

Electrostatics from Laplacian Eigenbasis for Neural Network Interatomic Potentials
by: Zhdanov, Maksim, et al.
Published: (2025)

Exponential Family Variational Flow Matching for Tabular Data Generation
by: Guzmán-Cordero, Andrés, et al.
Published: (2025)

VISA: Variational Inference with Sequential Sample-Average Approximations
by: Zimmermann, Heiko, et al.
Published: (2024)

Pawsterior: Variational Flow Matching for Structured Simulation-Based Inference
by: Carrasco-Pollo, Jorge, et al.
Published: (2026)

BSA: Ball Sparse Attention for Large-scale Geometries
by: Brita, Catalin E., et al.
Published: (2025)

CORDS: Continuous Representations of Discrete Structures
by: Veljković, Tin Hadži, et al.
Published: (2026)

Adaptive Mesh-Quantization for Neural PDE Solvers
by: Dool, Winfried van den, et al.
Published: (2025)

Efficient Parallelization Layouts for Large-Scale Distributed Model Training
by: Hagemann, Johannes, et al.
Published: (2023)

Identity Curvature Laplace Approximation for Improved Out-of-Distribution Detection
by: Zhdanov, Maksim, et al.
Published: (2023)

Variational Flow Matching for Graph Generation
by: Eijkelboom, Floor, et al.
Published: (2024)

Protocol Models: Scaling Decentralized Training with Communication-Efficient Model Parallelism
by: Ramasinghe, Sameera, et al.
Published: (2025)

Automated Attention Pattern Discovery at Scale in Large Language Models
by: Katzy, Jonathan, et al.
Published: (2026)

Inverse Concave-Utility Reinforcement Learning is Inverse Game Theory
by: Çelikok, Mustafa Mert, et al.
Published: (2024)

Sample-Efficient "Clustering and Conquer" Procedures for Parallel Large-Scale Ranking and Selection
by: Zhang, Zishi, et al.
Published: (2024)

Temporally Multi-Scale Sparse Self-Attention for Physical Activity Data Imputation
by: Wei, Hui, et al.
Published: (2024)

AMDP: Asynchronous Multi-Directional Pipeline Parallelism for Large-Scale Models Training
by: Chen, Ling, et al.
Published: (2026)

Kernel-Gradient Drifting Models
by: Esteban-Casadevall, Maria, et al.
Published: (2026)

Entropy Coding of Unordered Data Structures
by: Kunze, Julius, et al.
Published: (2024)

Piper: Efficient Large-Scale MoE Training via Resource Modeling and Pipelined Hybrid Parallelism
by: Dash, Sajal, et al.
Published: (2026)

Scaling Parallel Sequence Models to Foundation-Scale Vision Encoders
by: Jiang, Yitong, et al.
Published: (2026)

AdS-GNN -- a Conformally Equivariant Graph Neural Network
by: Zhdanov, Maksim, et al.
Published: (2025)

Diversifying Deep Ensembles: A Saliency Map Approach for Enhanced OOD Detection, Calibration, and Accuracy
by: Dereka, Stanislav, et al.
Published: (2023)

The Traitors: Deception and Trust in Multi-Agent Language Model Simulations
by: Curvo, Pedro M. P.
Published: (2025)

Untied Ulysses: Memory-Efficient Context Parallelism via Headwise Chunking
by: Ghadia, Ravi, et al.
Published: (2026)

Parallel Scaling Law for Language Models
by: Chen, Mouxiang, et al.
Published: (2025)

Large Scale Multi-Task Bayesian Optimization with Large Language Models
by: Zeng, Yimeng, et al.
Published: (2025)

MoE Parallel Folding: Heterogeneous Parallelism Mappings for Efficient Large-Scale MoE Model Training with Megatron Core
by: Liu, Dennis, et al.
Published: (2025)

Two-dimensional Sparse Parallelism for Large Scale Deep Learning Recommendation Model Training
by: Zhang, Xin, et al.
Published: (2025)

Multi-Scale and Multimodal Species Distribution Modeling
by: van Tiel, Nina, et al.
Published: (2024)

Scaling Attention via Feature Sparsity
by: Xie, Yan, et al.
Published: (2026)

Learnable Multipliers: Freeing the Scale of Language Model Matrix Layers
by: Velikanov, Maksim, et al.
Published: (2026)

Categorical Flow Maps
by: Roos, Daan, et al.
Published: (2026)

Riemannian Variational Flow Matching for Material and Protein Design
by: Zaghen, Olga, et al.
Published: (2025)

Clifford-Steerable Convolutional Neural Networks
by: Zhdanov, Maksim, et al.
Published: (2024)

Predictive Scaling Laws for Efficient GRPO Training of Large Reasoning Models
by: Nimmaturi, Datta, et al.
Published: (2025)