1,150+ open-access research outputs.
Federated Unlearning (FU) is an emerging paradigm in Federated Learning (FL) that enables participating clients to fully remove their contributions from a trained global model, driven by data protecti…
FU Ori outbursts are thought to play a key role in stellar mass assembly and in the chemistry of protoplanetary disks during the early formation of stars. However, uncertainties remain regarding the u…
The consequences of a protoplanetary disk collision with a gas stream are being studied using three-dimensional numerical gas-dynamic simulation. The influence of orbital parameters and the stream mas…
Understanding scientific papers requires more than answering isolated questions or summarizing content. It involves an integrated reasoning process that grounds textual and visual information, interpr…
Eruptive accretion events are expected to play an important role in the mass buildup stage of individual star formation. FU Ori objects (FUors) experience the most extreme eruptive outbursts, which ra…
Context. Episodic accretion in young stellar objects (YSOs) is thought to play a critical role in addressing the "luminosity problem" associated with star formation. However, optical surveys tend to b…
Point-based Neural Networks (PNNs) have become a key approach for point cloud processing. However, a core operation in these models, Farthest Point Sampling (FPS), often introduces significant inferen…
In this paper, we study the Fu\v{c}ik spectrum for the operator with rapidly increasing weight, which is defined as a set $\Sigma$ comprising those $(\alpha, \beta) \in \mathbb{R}^2$ such that \begin{…
Direct numerical simulations are performed to investigate the combined effects of surface roughness and wall heat transfer on spatially developing compressible turbulent boundary layers at $Ma=2.5$. T…
We investigate how resolving the inner few astronomical units of a massive protostellar disk affects the migration, disruption, and accretion signatures of an inward-moving fragment. In particular, we…
Video depth estimation is essential for providing 3D scene structure in applications ranging from autonomous driving to mixed reality. Current end-to-end video depth models have established state-of-t…
This thesis is an exposition of Ollivier-Ricci Curvature of metric spaces as introduced by Yann Ollivier, which is based upon the 1-Wasserstein Distance and optimal transport theory. We present some o…
Conventional 2D fluorescence imaging in glioma surgery cannot separate intrinsic fluorophore strength from attenuation with depth, creating depth-intensity ambiguity that can compromise assessment of …
We employed molecular dynamics simulations (MD) and Bennett's acceptance ratio method to compute the free energy of transfer (Delta G_trans) of phenol, methane, and 5-fluorouracil (5-FU) between bulk …
The cyclic sieving phenomenon was introduced by Reiner, Stanton and White in 2004 as a generalization of Stembridge's $q=-1$ phenomenon. In a paper from 2008, Eu and Fu studied many occurrences of thi…
Correlated electron systems with topological flat bands show great promise in exploring exotic quantum phenomena. However, such crystalline materials remain rare. Here we report the discovery of a nov…
The primary objective of research in modern sensor technologies is to develop innovative detection methods for the rapid analysis of complex molecular systems. The present work demonstrates that the q…
Distributed AI and IoT applications increasingly execute across heterogeneous resources spanning end devices, edge/fog infrastructure, and cloud platforms, often under different administrative domains…
Fully unsupervised deep generative modeling (FU-DGM) is promising for compressively sampled MRI (CS-MRI) when training data or compute are limited. Classical FU-DGMs such as DIP and INR rely on archit…
Current humanoid motion tracking systems can execute routine and moderately dynamic behaviors, yet significant gaps remain near hardware performance limits and algorithmic robustness boundaries. Marti…
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