Lalla Mouatadid

University of Toronto

H-index: 5

North America-Canada

About Lalla Mouatadid

Lalla Mouatadid, With an exceptional h-index of 5 and a recent h-index of 5 (since 2020), a distinguished researcher at University of Toronto, specializes in the field of Graph Theory, Algorithms, Theoretical Computer Science..

His recent articles reflect a diverse array of research interests and contributions to the field:

Modeling and managing affinity networks

-Modules in Graphs

SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models

DECDM: Document Enhancement using Cycle-Consistent Diffusion Models

Scalable weak-supervised learning with domain constraints

Model based document image enhancement

Hybrid artificial intelligence generated actionable recommendations

A new graph parameter to measure linearity

Lalla Mouatadid Information

University	University of Toronto
Position	___
Citations(all)	102
Citations(since 2020)	73
Cited By	56
hIndex(all)	5
hIndex(since 2020)	5
i10Index(all)	3
i10Index(since 2020)	2
Email	Access Email
University Profile Page	University of Toronto
Google Scholar	View Google Scholar Profile

Lalla Mouatadid Skills & Research Interests

Graph Theory

Algorithms

Theoretical Computer Science.

Lalla Mouatadid

University of Toronto

About Lalla Mouatadid

Lalla Mouatadid Information

Lalla Mouatadid Skills & Research Interests

Top articles of Lalla Mouatadid

Modeling and managing affinity networks

-Modules in Graphs

Lalla Mouatadid

SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models

Xiang Gao

Jiaxin Zhang

Lalla Mouatadid

DECDM: Document Enhancement using Cycle-Consistent Diffusion Models

Jiaxin Zhang

Lalla Mouatadid

Scalable weak-supervised learning with domain constraints

Model based document image enhancement

Hybrid artificial intelligence generated actionable recommendations

A new graph parameter to measure linearity

Lalla Mouatadid

RE: Region-Aware Relation Extraction from Visually Rich Documents

Sijia Wang

Lalla Mouatadid

Lifu Huang

Optimizing questions to retain engagement

A Scalable Technique for Weak-Supervised Learning with Domain Constraints

Lalla Mouatadid

A general algorithmic scheme for combinatorial decompositions with application to modular decompositions of hypergraphs

Lalla Mouatadid

Mining frequent patterns on knowledge graphs

Lalla Mouatadid

Storage structure for pattern mining

Verifiable Cacheable Calclulations

Maximum induced matching algorithms via vertex ordering characterizations

Lalla Mouatadid

Approximating modular decomposition is hard

Lalla Mouatadid