Cover Image

Towards Fast Coarse-graining and Equation Discovery with Foundation Inference Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Hinz, Manuel, Mauel, Maximilian, Seifner, Patrick, Berghaus, David, Cvejoski, Kostadin, Sanchez, Ramses J.
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

Towards Foundation Inference Models that Learn ODEs In-Context
by: Mauel, Maximilian, et al.
Published: (2025)

On Foundation Models for Temporal Point Processes to Accelerate Scientific Discovery
by: Berghaus, David, et al.
Published: (2025)

In-Context Learning of Stochastic Differential Equations with Foundation Inference Models
by: Seifner, Patrick, et al.
Published: (2025)

Foundation Inference Models for Markov Jump Processes
by: Berghaus, David, et al.
Published: (2024)

In-Context Learning of Temporal Point Processes with Foundation Inference Models
by: Berghaus, David, et al.
Published: (2025)

Foundation Inference Models for Ordinary Differential Equations
by: Mauel, Maximilian, et al.
Published: (2026)

Zero-shot Imputation with Foundation Inference Models for Dynamical Systems
by: Seifner, Patrick, et al.
Published: (2024)

Learning the Signature of Memorization in Autoregressive Language Models
by: Ilić, David, et al.
Published: (2026)

EVIL: Evolving Interpretable Algorithms for Zero-Shot Inference on Event Sequences and Time Series with LLMs
by: Berghaus, David
Published: (2026)

Powerful Training-Free Membership Inference Against Autoregressive Language Models
by: Ilić, David, et al.
Published: (2026)

Multi-Modal Vision vs. Text-Based Parsing: Benchmarking LLM Strategies for Invoice Processing
by: Berghaus, David, et al.
Published: (2025)

Beyond Reinforcement Learning: Fast and Scalable Quantum Circuit Synthesis
by: Theißinger, Lukas, et al.
Published: (2026)

Closure Discovery for Coarse-Grained Partial Differential Equations Using Grid-based Reinforcement Learning
by: von Bassewitz, Jan-Philipp, et al.
Published: (2024)

Effortless, Simulation-Efficient Bayesian Inference using Tabular Foundation Models
by: Vetter, Julius, et al.
Published: (2025)

Arrow: A Foundation Model for Causal Discovery
by: Thompson, Ryan, et al.
Published: (2026)

Domain-Adaptation through Synthetic Data: Fine-Tuning Large Language Models for German Law
by: Bashir, Ali Hamza, et al.
Published: (2026)

Towards a Foundation Model for Partial Differential Equations Across Physics Domains
by: Soares, Eduardo, et al.
Published: (2025)

Fast-PGM: Fast Probabilistic Graphical Model Learning and Inference
by: Jiang, Jiantong, et al.
Published: (2024)

Coarse graining and reduced order models for plume ejection dynamics
by: Salas, Ike Griss, et al.
Published: (2025)

Towards Causal Foundation Model: on Duality between Causal Inference and Attention
by: Zhang, Jiaqi, et al.
Published: (2023)

EDC: Equation Discovery for Classification
by: Toussaint, Guus, et al.
Published: (2025)

Multi-Task Equation Discovery
by: Bee, S C, et al.
Published: (2025)

Amortized In-Context Mixed Effect Transformer Models: A Zero-Shot Approach for Pharmacokinetics
by: Marin, César Ali Ojeda, et al.
Published: (2025)

Towards a Foundation Model for Partial Differential Equations: Multi-Operator Learning and Extrapolation
by: Sun, Jingmin, et al.
Published: (2024)

Resource-efficient Inference with Foundation Model Programs
by: Nie, Lunyiu, et al.
Published: (2025)

Optimistic Task Inference for Behavior Foundation Models
by: Rupf, Thomas, et al.
Published: (2025)

Towards Reasoning for PDE Foundation Models: A Reward-Model-Driven Inference-Time-Scaling Algorithm
by: Mansingh, Siddharth, et al.
Published: (2025)

Prior-Guided Symbolic Regression: Towards Scientific Consistency in Equation Discovery
by: Xiao, Jing, et al.
Published: (2026)

CHORUS: Foundation Models for Unified Data Discovery and Exploration
by: Kayali, Moe, et al.
Published: (2023)

Towards Foundation Models for Critical Care Time Series
by: Burger, Manuel, et al.
Published: (2024)

Symmetry-Informed Governing Equation Discovery
by: Yang, Jianke, et al.
Published: (2024)

xLSTM 7B: A Recurrent LLM for Fast and Efficient Inference
by: Beck, Maximilian, et al.
Published: (2025)

SLEM: Machine Learning for Path Modeling and Causal Inference with Super Learner Equation Modeling
by: Vowels, Matthew J.
Published: (2023)

Towards a Physics Foundation Model
by: Wiesner, Florian, et al.
Published: (2025)

History Rhymes: Macro-Contextual Retrieval for Robust Financial Forecasting
by: Khanna, Sarthak, et al.
Published: (2025)

Fast Adaptation with Behavioral Foundation Models
by: Sikchi, Harshit, et al.
Published: (2025)

Multimodal Foundation Models for Material Property Prediction and Discovery
by: Moro, Viggo, et al.
Published: (2023)

Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems
by: Kramer, Stefan, et al.
Published: (2023)

Foundation Models for Discovery and Exploration in Chemical Space
by: Wadell, Alexius, et al.
Published: (2025)

Mechanistic PDE Networks for Discovery of Governing Equations
by: Pervez, Adeel, et al.
Published: (2025)