Search Results for author: Ghulam Rasool

Found 8 papers, 1 papers with code

Transformers in Time-series Analysis: A Tutorial

no code implementations28 Apr 2022 Sabeen Ahmed, Ian E. Nielsen, Aakash Tripathi, Shamoon Siddiqui, Ghulam Rasool, Ravi P. Ramachandran

Transformer architecture has widespread applications, particularly in Natural Language Processing and computer vision.

Time Series Time Series Analysis

Self-Compression in Bayesian Neural Networks

no code implementations10 Nov 2021 Giuseppina Carannante, Dimah Dera, Ghulam Rasool, Nidhal C. Bouaynaya

We show that Bayesian neural networks automatically discover redundancy in model parameters, thus enabling self-compression, which is linked to the propagation of uncertainty through the layers of the network.

BIG-bench Machine Learning

Dilated Inception U-Net (DIU-Net) for Brain Tumor Segmentation

no code implementations15 Aug 2021 Daniel E. Cahall, Ghulam Rasool, Nidhal C. Bouaynaya, Hassan M. Fathallah-Shaykh

Magnetic resonance imaging (MRI) is routinely used for brain tumor diagnosis, treatment planning, and post-treatment surveillance.

Brain Tumor Segmentation Tumor Segmentation

Robust Explainability: A Tutorial on Gradient-Based Attribution Methods for Deep Neural Networks

no code implementations23 Jul 2021 Ian E. Nielsen, Dimah Dera, Ghulam Rasool, Nidhal Bouaynaya, Ravi P. Ramachandran

Later, we discuss how gradient-based methods can be evaluated for their robustness and the role that adversarial robustness plays in having meaningful explanations.

Adversarial Robustness

Exploring Robust Architectures for Deep Artificial Neural Networks

1 code implementation30 Jun 2021 Asim Waqas, Ghulam Rasool, Hamza Farooq, Nidhal C. Bouaynaya

The architectures of deep artificial neural networks (DANNs) are routinely studied to improve their predictive performance.

Image Classification Neural Architecture Search +1

Constrained State Estimation -- A Review

no code implementations10 Jul 2018 Nesrine Amor, Ghulam Rasool, Nidhal C. Bouaynaya

The real-world applications in signal processing generally involve estimating the system state or parameters in nonlinear, non-Gaussian dynamic systems.

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