activity
20242026
most citedIntegrating Probabilistic Trees and Causal Networks for Clinical and Epidemiological Data

1 citations · 2 across the 6 of their papers we have counts for

collaborators

7 papers

math.GM2026

Polynomial -contraction: A unified approach with Application

Md Hasanuzzaman, Stojan N. Radenović

In this paper, we introduce polynomial -contraction by unifying the ideas of polynomial contraction and -contraction and also provide demonstrative exampl…

cs.CL2026

Rethinking Sign Language Translation: The Impact of Signer Dependence on Model Evaluation

Keren Artiaga, Sabyasachi Kamila, Haithem Afli +2

Sign Language Translation has advanced with deep learning, yet evaluations remain largely signer-dependent, with overlapping signers across train/dev/test. This raises concerns abo…

cs.CL2026

The Influence of Iconicity in Transfer Learning for Sign Language Recognition

Keren Artiaga, Conor Lynch, Haithem Afli +1

Most sign language recognition research relies on Transfer Learning (TL) from vision-based datasets such as ImageNet. Some extend this to alternatively available language datasets,…

cs.CL2025

CAuSE: Decoding Multimodal Classifiers using Faithful Natural Language Explanation

Dibyanayan Bandyopadhyay, Soham Bhattacharjee, Mohammed Hasanuzzaman +1

Multimodal classifiers function as opaque black box models. While several techniques exist to interpret their predictions, very few of them are as intuitive and accessible as natur…

cs.LG2025★ 1 cited

Integrating Probabilistic Trees and Causal Networks for Clinical and Epidemiological Data

Sheresh Zahoor, Pietro Liò, Gaël Dias +1

Healthcare decision-making requires not only accurate predictions but also insights into how factors influence patient outcomes. While traditional Machine Learning (ML) models exce…

cs.CL2024

Seeing Through VisualBERT: A Causal Adventure on Memetic Landscapes

Dibyanayan Bandyopadhyay, Mohammed Hasanuzzaman, Asif Ekbal

Detecting offensive memes is crucial, yet standard deep neural network systems often remain opaque. Various input attribution-based methods attempt to interpret their behavior, but…

cs.LG2024★ 1 cited

Investigating the validity of structure learning algorithms in identifying risk factors for intervention in patients with diabetes

Sheresh Zahoor, Anthony C. Constantinou, Tim M Curtis +1

Diabetes, a pervasive and enduring health challenge, imposes significant global implications on health, financial healthcare systems, and societal well-being. This study undertakes…