Shoaib Ahmed Siddiqui

Orcid: 0000-0003-4600-7331

According to our database1, Shoaib Ahmed Siddiqui authored at least 38 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Blockwise Self-Supervised Learning at Scale.
Trans. Mach. Learn. Res., 2024

Exploring the design space of deep-learning-based weather forecasting systems.
CoRR, 2024

On Evaluating LLMs' Capabilities as Functional Approximators: A Bayesian Perspective.
CoRR, 2024

Permissive Information-Flow Analysis for Large Language Models.
CoRR, 2024

Protecting against simultaneous data poisoning attacks.
CoRR, 2024

A deeper look at depth pruning of LLMs.
CoRR, 2024

2023
Investigating the Nature of 3D Generalization in Deep Neural Networks.
CoRR, 2023

Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
A Simple Yet Fully Adaptive PSO Algorithm for Global Peak Tracking of Photovoltaic Array Under Partial Shading Conditions.
IEEE Trans. Ind. Electron., 2022

Domain Generalization for Robust Model-Based Offline Reinforcement Learning.
CoRR, 2022

Improving Health Mentioning Classification of Tweets using Contrastive Adversarial Training.
CoRR, 2022

Improving Health Mention Classification of Social Media Content Using Contrastive Adversarial Training.
IEEE Access, 2022

Revisiting the Shape-Bias of Deep Learning for Dermoscopic Skin Lesion Classification.
Proceedings of the Medical Image Understanding and Analysis - 26th Annual Conference, 2022

Are Deep Models Robust against Real Distortions? A Case Study on Document Image Classification.
Proceedings of the 26th International Conference on Pattern Recognition, 2022

2021
TSInsight: A Local-Global Attribution Framework for Interpretability in Time Series Data.
Sensors, 2021

Identifying Layers Susceptible to Adversarial Attacks.
CoRR, 2021

Self-Supervised Representation Learning for Document Image Classification.
IEEE Access, 2021

Analyzing the Potential of Zero-Shot Recognition for Document Image Classification.
Proceedings of the 16th International Conference on Document Analysis and Recognition, 2021

Understanding and Mitigating the Impact of Model Compression for Document Image Classification.
Proceedings of the 16th International Conference on Document Analysis and Recognition, 2021

2020
Benchmarking Deep Learning Models for Classification of Book Covers.
SN Comput. Sci., 2020

Reliable Model Compression via Label-Preservation-Aware Loss Functions.
CoRR, 2020

Confident Classification Using a Hybrid Between Deterministic and Probabilistic Convolutional Neural Networks.
IEEE Access, 2020

Interpreting Deep Models through the Lens of Data.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Benchmarking Adversarial Attacks and Defenses for Time-Series Data.
Proceedings of the Neural Information Processing - 27th International Conference, 2020

2019
FuseAD: Unsupervised Anomaly Detection in Streaming Sensors Data by Fusing Statistical and Deep Learning Models.
Sensors, 2019

Correction to: Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning.
BMC Medical Informatics Decis. Mak., 2019

Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning.
BMC Medical Informatics Decis. Mak., 2019

TSViz: Demystification of Deep Learning Models for Time-Series Analysis.
IEEE Access, 2019

DeepAnT: A Deep Learning Approach for Unsupervised Anomaly Detection in Time Series.
IEEE Access, 2019

Rethinking Semantic Segmentation for Table Structure Recognition in Documents.
Proceedings of the 2019 International Conference on Document Analysis and Recognition, 2019

DeepTabStR: Deep Learning based Table Structure Recognition.
Proceedings of the 2019 International Conference on Document Analysis and Recognition, 2019

TSXplain: Demystification of DNN Decisions for Time-Series Using Natural Language and Statistical Features.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019 - 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17-19, 2019, Proceedings, 2019

DeepEX: Bridging the Gap Between Knowledge and Data Driven Techniques for Time Series Forecasting.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Deep Learning, 2019

OGaze: Gaze Prediction in Egocentric Videos for Attentional Object Selection.
Proceedings of the 2019 Digital Image Computing: Techniques and Applications, 2019

KINN: Incorporating Expert Knowledge in Neural Networks.
Proceedings of the AAAI 2019 Spring Symposium on Combining Machine Learning with Knowledge Engineering (AAAI-MAKE 2019) Stanford University, 2019

2018
DeCNT: Deep Deformable CNN for Table Detection.
IEEE Access, 2018

Deep One-Class Classification.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
A wearable sensor based multi-criteria-decision-system for real-time seizure detection.
Proceedings of the 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017


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