10 citations · 10 across the 5 of their papers we have counts for
5 papers
E-TCAV: Formalizing Penultimate Proxies for Efficient Concept Based Interpretability
Hasib Aslam, Muhammad Ali Chattha, Muhammad Taha Mukhtar +3
TCAV (Testing with Concept Activation Vectors) is an interpretability method that assesses the alignment between the internal representations of a trained neural network and human-…
SLUM-i: Semi-supervised Learning for Urban Mapping of Informal Settlements and Data Quality Benchmarking
Muhammad Taha Mukhtar, Syed Musa Ali Kazmi, Khola Naseem +5
Very-high-resolution remote-sensing imagery provides a scalable basis for delineating informal settlements, but sparse annotations, severe imbalance between informal-settlement and…
KENN: Enhancing Deep Neural Networks by Leveraging Knowledge for Time Series Forecasting
Muhammad Ali Chattha, Ludger van Elst, Muhammad Imran Malik +2
End-to-end data-driven machine learning methods often have exuberant requirements in terms of quality and quantity of training data which are often impractical to fulfill in real-w…
A Survey on Knowledge integration techniques with Artificial Neural Networks for seq-2-seq/time series models
Pramod Vadiraja, Muhammad Ali Chattha
In recent years, with the advent of massive computational power and the availability of huge amounts of data, Deep neural networks have enabled the exploration of uncharted areas i…
KINN: Incorporating Expert Knowledge in Neural Networks
Muhammad Ali Chattha, Shoaib Ahmed Siddiqui, Muhammad Imran Malik +3
The promise of ANNs to automatically discover and extract useful features/patterns from data without dwelling on domain expertise although seems highly promising but comes at the c…