output
20102026
most citedA Review of Deep Transfer Learning and Recent Advancements

686 citations

8 papers

astro-ph.EP2026

An Agnostic Machine Learning Model of Photosynthetic Habitability

Callum Gray, Cassandra Hall, Stefano Santabarbara +5

The search for exoplanet biosignatures is guided by whether planetary environments can sustain photosynthesis. As such, the Photosynthetic Habitable Zone (PHZ) was recently propose…

cs.CV2024★ 13 cited

Dual-Task Vision Transformer for Rapid and Accurate Intracerebral Hemorrhage CT Image Classification

Jialiang Fan, Xinhui Fan, Chengyan Song +4

Intracerebral hemorrhage (ICH) is a severe and sudden medical condition caused by the rupture of blood vessels in the brain, leading to permanent damage to brain tissue and often r…

cs.LG2022★ 686 cited

EXPANSE: A Deep Continual / Progressive Learning System for Deep Transfer Learning

Mohammadreza Iman, John A. Miller, Khaled Rasheed +2

Deep transfer learning techniques try to tackle the limitations of deep learning, the dependency on extensive training data and the training costs, by reusing obtained knowledge. H…

cs.LG2022★ 686 cited

A Review of Deep Transfer Learning and Recent Advancements

Mohammadreza Iman, Khaled Rasheed, Hamid R. Arabnia

Deep learning has been the answer to many machine learning problems during the past two decades. However, it comes with two major constraints: dependency on extensive labeled data…

math.CO2019

Universal Gröbner Bases of Toric Ideals of Combinatorial Neural Codes

Melissa Beer, Robert Davis, Thomas Elgin +5

In the 1970s, O'Keefe and Dostrovsky discovered that certain neurons, called place cells, in an animal's brain are tied to its location within its arena. A combinatorial neural cod…

math.PR2017

Upper and Lower Bounds on the Speed of a One Dimensional Excited Random Walk

Erin Bossen, Brian Kidd, Owen Levin +3

Excited random walks (ERWs) are a self-interacting non-Markovian random walk in which the future behavior of the walk is influenced by the number of times the walk has previously v…