output
20022025
most citedEnergy Loss and Flow of Heavy Quarks in Au+Au Collisions at sqrt(s_NN) = 200 GeV

593 citations

Showing 2024Show all

15 papers · 1 filter

cs.CR20241 cited

MOFHEI: Model Optimizing Framework for Fast and Efficient Homomorphically Encrypted Neural Network Inference

Parsa Ghazvinian, Robert Podschwadt, Prajwal Panzade +2

Due to the extensive application of machine learning (ML) in a wide range of fields and the necessity of data privacy, privacy-preserving machine learning (PPML) solutions have rec…

q-fin.CP2024

Do Activists Align with Larger Mutual Funds?

Manish Jha

This paper demonstrates that hedge funds tend to design their activist campaigns to align with the preferences and ideologies of institutions holding large stakes in the target com…

astro-ph.HE20244 cited

Multi-wavelength spectroscopic analysis of the ULX Holmberg II X-1 and its nebula suggests the presence of a heavy black hole accreting from a B-type donor

S. Reyero Serantes, L. Oskinova, W. -R. Hamann +11

Ultra-luminous X-ray sources (ULXs) are high-mass X-ray binaries with an X-ray luminosity above erg s. These ULXs can be powered by black holes that are more massi…

cs.LG2024

Towards Hybrid Embedded Feature Selection and Classification Approach with Slim-TSF

Anli Ji, Chetraj Pandey, Berkay Aydin

Traditional solar flare forecasting approaches have mostly relied on physics-based or data-driven models using solar magnetograms, treating flare predictions as a point-in-time cla…

hep-ex2024

Multiplicity dependent and production at forward and backward rapidity in collisions at GeV

PHENIX Collaboration, N. J. Abdulameer, U. Acharya +298

The and charmonium states, composed of quark pairs and known since the 1970s, are widely believed to serve as ideal probes to test quantum chromodynamics i…

cs.CV202410 cited

Deep learning for automated detection of breast cancer in deep ultraviolet fluorescence images with diffusion probabilistic model

Sepehr Salem Ghahfarokhi, Tyrell To, Julie Jorns +3

Data limitation is a significant challenge in applying deep learning to medical images. Recently, the diffusion probabilistic model (DPM) has shown the potential to generate high-q…