Cover Image

Inverse analysis of granular flows using differentiable graph neural network simulator

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Choi, Yongjin, Kumar, Krishna
Format:	Preprint
Published:	2024
Subjects:	Geophysics Machine Learning I.6.8
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Accelerating wave simulations with neural dispersion correctors
by: Rincón, Felipe, et al.
Published: (2025)

Total Generalized Variation regularization closes the gap between neural-eld and classical methods in seismic travel-time tomography
by: Kurosawa, Isao
Published: (2026)

An Improved Adaptive PID Optimizer with Enhanced Convergence and Stability for Deep Learning
by: Saini, Saurabh, et al.
Published: (2026)

Modeling liquefaction-induced runout of a tailings dam using a hybrid finite element and material point method approach
by: Sordo, Brent, et al.
Published: (2024)

Evolving machine learning workflows through interactive AutoML
by: Barbudo, Rafael, et al.
Published: (2024)

Artificial intelligence and downscaling global climate model future projections
by: Benestad, Rasmus E.
Published: (2026)

CellARC: Measuring Intelligence with Cellular Automata
by: Lžičař, Miroslav
Published: (2025)

SMOSE: Sparse Mixture of Shallow Experts for Interpretable Reinforcement Learning in Continuous Control Tasks
by: Vincze, Mátyás, et al.
Published: (2024)

A Comparison Between Decision Transformers and Traditional Offline Reinforcement Learning Algorithms
by: Caunhye, Ali Murtaza, et al.
Published: (2025)

VDW-GNNs: Vector diffusion wavelets for geometric graph neural networks
by: Johnson, David R., et al.
Published: (2025)

Perspective: Towards sustainable exploration of chemical spaces with machine learning
by: Sandonas, Leonardo Medrano, et al.
Published: (2026)

Adaptive Mixture Importance Sampling for Automated Ads Auction Tuning
by: Jia, Yimeng, et al.
Published: (2024)

Towards geological inference with process-based and deep generative modeling, part 1: training on fluvial deposits
by: Rongier, Guillaume, et al.
Published: (2025)

Towards geological inference with process-based and deep generative modeling, part 2: inversion of fluvial deposits and latent-space disentanglement
by: Rongier, Guillaume, et al.
Published: (2025)

Quenching statistics in Si and Ge SPADs using particle Monte Carlo simulation
by: Dollfus, Philippe, et al.
Published: (2025)

A graph neural network-based model with Out-of-Distribution Robustness for enhancing Antiretroviral Therapy Outcome Prediction for HIV-1
by: Di Teodoro, Giulia, et al.
Published: (2023)

WAKESET: A Large-Scale, High-Reynolds Number Flow Dataset for Machine Learning of Turbulent Wake Dynamics
by: Cooper-Baldock, Zachary, et al.
Published: (2026)

4D-Var using Hessian approximation and backpropagation applied to automatically-differentiable numerical and machine learning models
by: Solvik, Kylen, et al.
Published: (2024)

SafeRL-Lite: A Lightweight, Explainable, and Constrained Reinforcement Learning Library
by: Mishra, Satyam, et al.
Published: (2025)

KL-Regularised Q-Learning: A Token-level Action-Value perspective on Online RLHF
by: Brown, Jason R, et al.
Published: (2025)

Foundation Models as World Models: A Foundational Study in Text-Based GridWorlds
by: Sasso, Remo, et al.
Published: (2025)

Efficient Contextual Preferential Bayesian Optimization with Historical Examples
by: Khan, Farha A., et al.
Published: (2022)

Modeling and Controlling Deployment Reliability under Temporal Distribution Shift
by: Rahman, Naimur, et al.
Published: (2026)

Exploration with Foundation Models: Capabilities, Limitations, and Hybrid Approaches
by: Sasso, Remo, et al.
Published: (2025)

GoldenStart: Q-Guided Priors and Entropy Control for Distilling Flow Policies
by: Zhang, He, et al.
Published: (2026)

Spatio-temporal, multi-field deep learning of shock propagation in meso-structured media
by: Fernández-Godino, M. Giselle, et al.
Published: (2025)

Adaptive Negative Scheduling for Graph Contrastive Learning
by: Ali, Adnan, et al.
Published: (2026)

Emotion-Inspired Learning Signals (EILS): A Homeostatic Framework for Adaptive Autonomous Agents
by: Tiwari, Dhruv
Published: (2025)

The Impact of Data Characteristics on GNN Evaluation for Detecting Fake News
by: Karn, Isha, et al.
Published: (2025)

Statistical Guarantees for Lifelong Reinforcement Learning using PAC-Bayes Theory
by: Zhang, Zhi, et al.
Published: (2024)

Three-dimensional inversion of gravity data using implicit neural representations and scientific machine learning
by: Mishra, Pankaj K, et al.
Published: (2025)

Diagnosing Failure Modes of Neural Operators Across Diverse PDE Families
by: Shikhman, Lennon
Published: (2026)

Neural Operators for Mathematical Modeling of Transient Fluid Flow in Subsurface Reservoir Systems
by: Sirota, Daniil D., et al.
Published: (2025)

From Imitation to Interaction: Mastering Game of Schnapsen with Shallow Reinforcement Learning
by: Klačan, Ján, et al.
Published: (2026)

Mitigating Catastrophic Forgetting in Streaming Generative and Predictive Learning via Stateful Replay
by: Du, Wenzhang
Published: (2025)

Learning from Preferences and Mixed Demonstrations in General Settings
by: Brown, Jason R, et al.
Published: (2025)

Rapid training of Hamiltonian graph networks using random features
by: Rahma, Atamert, et al.
Published: (2025)

Resource-constrained Amazons chess decision framework integrating large language models and graph attention
by: Qian, Tianhao, et al.
Published: (2026)

METER: Multi-modal Evidence-based Thinking and Explainable Reasoning -- Algorithm and Benchmark
by: Yang, Xu, et al.
Published: (2025)

RG-TTA: Regime-Guided Meta-Control for Test-Time Adaptation in Streaming Time Series
by: Kumar, Indar, et al.
Published: (2026)