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Unified Multimodal models (UMMs) built on a single architecture have shown impressive performance in both understanding and generation. We identify a fundamental challenge that lies in inductive biases induced by distinct supervision…
The exploration of outflows in protobinary systems presents a challenging yet crucial endeavour, offering valuable insights into the dynamic interplay between protostars and their evolution. In this study, we examine the morphology and…
This paper introduces feature gradient flow, a new technique for interpreting deep learning models in terms of features that are understandable to humans. The gradient flow of a model locally defines nonlinear coordinates in the input data…
In the realm of computer graphics, the ability to learn continuously from non-stationary data streams while adapting to new visual patterns and mitigating catastrophic forgetting is of paramount importance. Existing approaches often…
Accurate machine-learning models for aerodynamic prediction are essential for accelerating shape optimization, yet remain challenging to develop for complex three-dimensional configurations due to the high cost of generating training data.…
By studying 7 objects in the Lupus clouds we aim to test if a coherence exists between commonly used evolutionary tracers. We present ALMA observations of the continuum and molecular line emission that probe the dense gas and dust of cores…
Galactic winds and mass outflows are observed both in nearby starburst galaxies and in high-redshift star-forming galaxies. In this paper we develop a simple analytic model to understand the observed superwind phenomenon. Our model is built…
We report the results of a series of AMR radiation-hydrodynamic simulations of the collapse of massive star forming clouds using the ORION code. These simulations are the first to include the feedback effects protostellar outflows, as well…
We present a comprehensive study on the physical and chemical structures of a chemically rich bipolar outflow in a high-mass star forming region IRAS 16272$-$4837 (SDC335), utilizing high-resolution spectral line data at 1.3 mm and 3 mm…
Amodal object completion is a complex task that involves predicting the invisible parts of an object based on visible segments and background information. Learning shape priors is crucial for effective amodal completion, but traditional…
Recent observations by the Atacama Large Millimeter/submillimeter Array (ALMA) of disks around young stars revealed distinct asymmetries in the dust continuum emission. In this work we want to study axisymmetric and non-axisymmetric…
Recent millimeter/sub-millimeter facilities have revealed the physical properties of filamentary molecular clouds in relation to high-mass star formation. A uniform survey of the nearest, face-on star-forming galaxy, the Large Magellanic…
Molecular orbital (MO) is one of the most fundamental concepts for molecules, relating to all branches of chemistry, while scanning tunneling microscopy (STM) has been widely recognized for its potential to measure the spatial distribution…
In order to explain grain growth to mm sized particles and their retention in outer regions of protoplanetary disks, as it is observed at sub-mm and mm wavelengths, we investigate if strong inhomogeneities in the gas density profiles can…
We investigate star-galaxy classification for astronomical surveys in the context of four methods enabling the interpretation of black-box machine learning systems. The first is outputting and exploring the decision boundaries as given by…
Protostellar outflows are one of the most outstanding features of star formation. Observational studies over the last several decades have successfully demonstrated that outflows are ubiquitously associated with low- and high-mass…
Scene flow prediction is a crucial underlying task in understanding dynamic scenes as it offers fundamental motion information. However, contemporary scene flow methods encounter three major challenges. Firstly, flow estimation solely based…
We investigate how misalignment between the core angular momentum and the large-scale magnetic field affects protostellar outflows, and whether a single protostellar system can drive multiple outflow components. We perform three-dimensional…
Point cloud analysis without pose priors is very challenging in real applications, as the orientations of point clouds are often unknown. In this paper, we propose a brand new point-set learning framework PRIN, namely, Pointwise…
Molecular dynamics (MD) simulations have become indispensable for exploring tribological deformation patterns at the atomic scale. However, transforming the resulting high-dimensional data into interpretable deformation pattern maps remains…