Cover Image

Latent Representation Learning of Multi-scale Thermophysics: Application to Dynamics in Shocked Porous Energetic Material

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Azarfar, Shahab, Choi, Joseph B., Nguyen, Phong CH., Nguyen, Yen T., Seshadri, Pradeep, Udaykumar, H. S., Baek, Stephen
Format:	Preprint
Published:	2025
Subjects:	Computational Physics Machine Learning I.2.6
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

PARCv2: Physics-aware Recurrent Convolutional Neural Networks for Spatiotemporal Dynamics Modeling
by: Nguyen, Phong C. H., et al.
Published: (2024)

Structured Contrastive Learning for Interpretable Latent Representations
by: Shen, Zhengyang, et al.
Published: (2025)

Deep Reinforcement Learning for Day-to-day Dynamic Tolling in Tradable Credit Schemes
by: Wu, Xiaoyi, et al.
Published: (2025)

Generative Pretrained Embedding and Hierarchical Irregular Time Series Representation for Daily Living Activity Recognition
by: Bouchabou, Damien, et al.
Published: (2024)

Latent Instruction Representation Alignment: defending against jailbreaks, backdoors and undesired knowledge in LLMs
by: Easley, Eric, et al.
Published: (2026)

Synergizing Deep Learning and Biological Heuristics for Extreme Long-Tail White Blood Cell Classification
by: Nguyen, Duc T., et al.
Published: (2026)

Learning Stochastic Nonlinear Dynamics with Embedded Latent Transfer Operators
by: Ke, Naichang, et al.
Published: (2025)

A physics-aware deep learning model for shear band formation around collapsing pores in shocked reactive materials
by: Cheng, Xinlun, et al.
Published: (2025)

Convolutional neural networks for large-scale dynamical modeling of itinerant magnets
by: Cheng, Xinlun, et al.
Published: (2023)

Bridging the Gap: An Intermediate Language for Enhanced and Cost-Effective Grapheme-to-Phoneme Conversion with Homographs with Multiple Pronunciations Disambiguation
by: Bertina, Abbas, et al.
Published: (2025)

What Do World Models Learn in RL? Probing Latent Representations in Learned Environment Simulators
by: Zhang, Xinyu
Published: (2026)

Latent Space Representation of Electricity Market Curves: Maintaining Structural Integrity
by: Výboh, Martin, et al.
Published: (2025)

LLM-as-a-Judge: Rapid Evaluation of Legal Document Recommendation for Retrieval-Augmented Generation
by: Pradhan, Anu, et al.
Published: (2025)

Reduced Order Modeling of Energetic Materials Using Physics-Aware Recurrent Convolutional Neural Networks in a Latent Space (LatentPARC)
by: Gray, Zoë J., et al.
Published: (2025)

Reduced‐Order Modeling of Energetic Materials Using Physics‐Aware Recurrent Convolutional Neural Networks in a Latent Space (LatentPARC)
by: Zoë J. Gray, et al.
Published: (2026)

Discrete Latent Structure in Neural Networks
by: Niculae, Vlad, et al.
Published: (2023)

Learning Can Converge Stably to the Wrong Belief under Latent Reliability
by: Zhang, Zhipeng, et al.
Published: (2026)

I-GLIDE: Input Groups for Latent Health Indicators in Degradation Estimation
by: Thil, Lucas, et al.
Published: (2025)

Latent Cache Flow: Model-to-Model Communication Without Text
by: Rossi, Maximillian, et al.
Published: (2026)

The intrinsic motivation of reinforcement and imitation learning for sequential tasks
by: Nguyen, Sao Mai
Published: (2024)

Optimizing Inference in Transformer-Based Models: A Multi-Method Benchmark
by: Ho, Siu Hang, et al.
Published: (2025)

Contrastive Representation Modeling for Anomaly Detection
by: Lunardi, Willian T., et al.
Published: (2025)

Connectivity-Aware Representations for Constrained Motion Planning via Multi-Scale Contrastive Learning
by: Jeon, Suhyun, et al.
Published: (2026)

More at Stake: How Payoff and Language Shape LLM Agent Strategies in Cooperation Dilemmas
by: Huynh, Trung-Kiet, et al.
Published: (2026)

Learning Transferable Predictability Representations
by: Goswami, Diyali, et al.
Published: (2026)

QuAnTS: Question Answering on Time Series
by: Divo, Felix, et al.
Published: (2025)

Fusing Rewards and Preferences in Reinforcement Learning
by: Khorasani, Sadegh, et al.
Published: (2025)

Scaling Laws for Neural Material Models
by: Trikha, Akshay, et al.
Published: (2025)

AI and Machine Learning Approaches for Predicting Nanoparticles Toxicity The Critical Role of Physiochemical Properties
by: Yousaf, Iqra
Published: (2024)

Learned Relay Representations for Forward-Thinking Discrete Diffusion Models
by: Rozonoyer, Benjamin, et al.
Published: (2026)

Representation learning with CGAN for casual inference
by: Weng, Zhaotian, et al.
Published: (2024)

Predicting and improving test-time scaling laws via reward tail-guided search
by: Li, Muheng, et al.
Published: (2026)

Intervening to Learn and Compose Causally Disentangled Representations
by: Markham, Alex, et al.
Published: (2025)

LaPro-DTA: Latent Dual-View Drug Representations and Salient Protein Feature Extraction for Generalizable Drug--Target Affinity Prediction
by: Dun, Zihan, et al.
Published: (2026)

Adaptive Latent-Space Constraints in Personalized Federated Learning
by: Ayromlou, Sana, et al.
Published: (2025)

GammaZero: Learning To Guide POMDP Belief Space Search With Graph Representations
by: Mangannavar, Rajesh, et al.
Published: (2025)

BLOCK-EM: Preventing Emergent Misalignment via Latent Blocking
by: Ustaomeroglu, Muhammed, et al.
Published: (2026)

Sparse Concept Anchoring for Interpretable and Controllable Neural Representations
by: Fraser, Sandy, et al.
Published: (2025)

ARCTraj: A Dataset and Benchmark of Human Reasoning Trajectories for Abstract Problem Solving
by: Kim, Sejin, et al.
Published: (2025)

Continuous Latent Contexts Enable Efficient Online Learning in Transformers
by: Anand, Emile, et al.
Published: (2026)