works on

From the 1 of 9 linked papers with an AI index.

collaborators

9 papers

physics.plasm-ph2026

A Shortcut to Statistically Steady-State Turbulence with Flow Matching

Gianluca Galletti, Gerald Gutenbrunner, William Hornsby +5

The paper presents GyroFlow, a latent generative model that directly creates statistically steady‑state snapshots of gyrokinetic turbulence, avoiding the costly transient simulatio…

cs.LG2026

A fully GPU-based workflow for building physics emulators of hypersonic flows

Fabian Paischer, Dylan Rubini, Deniz A. Bezgin +6

The ability to resolve complex physical phenomena with high fidelity and at low computational cost is central to addressing key challenges in modern engineering. A prime example li…

cs.LG2026

Meltdown: Circuits and Bifurcations in Point-Cloud-Conditioned 3D Diffusion Transformers

Maximilian Plattner, Fabian Paischer, Johannes Brandstetter +1

Sparse point clouds are a common input modality for 3D surface reconstruction, including in safety-critical settings such as surgical navigation and autonomous perception. Recent p…

cs.LG2026

ANTIC: Adaptive Neural Temporal In-situ Compressor

Sandeep S. Cranganore, Andrei Bodnar, Gianluca Galletti +2

The persistent storage requirements for high-resolution, spatiotemporally evolving fields governed by large-scale and high-dimensional partial differential equations (PDEs) have re…

physics.plasm-ph2026

Physics-Informed Neural Compression of High-Dimensional Plasma Data

Gianluca Galletti, Gerald Gutenbrunner, Sandeep S. Cranganore +6

High-fidelity scientific simulations are now producing unprecedented amounts of data, creating a storage and analysis bottleneck. A single simulation can generate tremendous data v…

cs.LG2025

Retrieval-Augmented Decision Transformer: External Memory for In-context RL

Thomas Schmied, Fabian Paischer, Vihang Patil +3

In-context learning (ICL) is the ability of a model to learn a new task by observing a few exemplars in its context. While prevalent in NLP, this capability has recently also been…