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ORCIDArnab Sharma
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2020 – today
- 2026
[c17]Daniel Vollmers
, Arnab Sharma, Axel-Cyrille Ngonga Ngomo:
Evaluating Noisy Optimization in Finetuning LMs for Neural Ranking. NLDB 2026: 237-251- [i13]Fadel Mamar Seydou, Arnab Sharma:
DeepFix: Debugging and Fixing Machine Learning Workflow using Agentic AI. CoRR abs/2603.14099 (2026) - [i12]Yasir Mahmood, Arnab Sharma, Axel-Cyrille Ngonga Ngomo, Balram Tiwari:
Rethinking Explanations: Formalizing Contrast in Description Logics. CoRR abs/2605.01442 (2026) - 2025
- [j1]Arnab Sharma, N'Dah Jean Kouagou, Axel-Cyrille Ngonga Ngomo:
Resilience in Knowledge Graph Embeddings. Trans. Graph Data Knowl. 3(2): 1:1-1:38 (2025) - [c16]Sourabh Kapoor, Arnab Sharma, Michael Röder, Caglar Demir, Axel-Cyrille Ngonga Ngomo:
Robustness Evaluation of Knowledge Graph Embedding Models Under Non-targeted Attacks. ESWC (1) 2025: 264-281 - [c15]Rupesh Sapkota, Caglar Demir, Arnab Sharma, Axel-Cyrille Ngonga Ngomo:
Parameter Averaging in Link Prediction. K-CAP 2025: 182-189 - [c14]Adel Memariani, Michael Röder, Arnab Sharma, Caglar Demir, Axel-Cyrille Ngonga Ngomo:
Link Prediction Under Non-targeted Attacks: Do Soft Labels Always Help? ISWC (1) 2025: 99-121 - [c13]Neha Pokharel, Arnab Sharma, Adel Memariani, Michael Röder, Axel-Cyrille Ngonga Ngomo:
LoSA: A Local Structural Approach to Adversarial Attack on the Knowledge Graph-based Question Answering System. Wikidata 2025 - [i11]Ding Ning, Varvara Vetrova, Karin R. Bryan, Yun Sing Koh, Andreas Voskou, N'Dah Jean Kouagou, Arnab Sharma:
Diving Deep: Forecasting Sea Surface Temperatures and Anomalies. CoRR abs/2501.05731 (2025) - [i10]Rupesh Sapkota, Caglar Demir, Arnab Sharma, Axel-Cyrille Ngonga Ngomo:
Parameter Averaging in Link Prediction. CoRR abs/2510.25361 (2025) - [i9]Arnab Sharma:
Learning to Retrieve with Weakened Labels: Robust Training under Label Noise. CoRR abs/2512.13237 (2025) - 2024
- [c12]Daniel F. Leite, Alisson Silva, Gabriella Casalino, Arnab Sharma, Danielle Fortunato, Axel-Cyrille Ngonga Ngomo:
EGNN-C+: Interpretable Evolving Granular Neural Network and Application in Classification of Weakly-Supervised EEG Data Streams. EAIS 2024: 1-10 - [c11]Daniel F. Leite, Arnab Sharma, Caglar Demir, Axel-Cyrille Ngonga Ngomo:
Interpretability Index Based on Balanced Volumes for Transparent Models and Agnostic Explainers. FUZZ 2024: 1-10 - [c10]Arnab Sharma, Daniel F. Leite, Caglar Demir, Axel-Cyrille Ngonga Ngomo:
Trading-Off Interpretability and Accuracy in Medical Applications: A Study Toward Optimal Explainability of Hoeffding Trees. FUZZ 2024: 1-10 - [c9]Ding Ning, Varvara Vetrova, Karin R. Bryan, Yun Sing Koh, Andreas Voskou, N'Dah Jean Kouagou, Arnab Sharma:
Diving Deep: Forecasting Sea Surface Temperatures and Anomalies. PKDD/ECML Workshops (4) 2024: 32-41 - [i8]Daniel Leite, Alisson Silva, Gabriella Casalino, Arnab Sharma, Danielle Fortunato, Axel-Cyrille Ngonga Ngomo:
EGNN-C+: Interpretable Evolving Granular Neural Network and Application in Classification of Weakly-Supervised EEG Data Streams. CoRR abs/2402.17792 (2024) - [i7]Caglar Demir, Arnab Sharma, Axel-Cyrille Ngonga Ngomo:
Adaptive Stochastic Weight Averaging. CoRR abs/2406.19092 (2024) - [i6]Sourabh Kapoor, Arnab Sharma, Michael Röder, Caglar Demir, Axel-Cyrille Ngonga Ngomo:
Performance Evaluation of Knowledge Graph Embedding Approaches under Non-adversarial Attacks. CoRR abs/2407.06855 (2024) - [i5]Caglar Demir, N'Dah Jean Kouagou, Arnab Sharma, Axel-Cyrille Ngonga Ngomo:
Inference over Unseen Entities, Relations and Literals on Knowledge Graphs. CoRR abs/2410.06742 (2024) - [i4]Arnab Sharma, N'Dah Jean Kouagou, Axel-Cyrille Ngonga Ngomo:
Resilience in Knowledge Graph Embeddings. CoRR abs/2410.21163 (2024) - 2023
- [b1]Arnab Sharma:
Testing of machine learning algorithms and models. University of Oldenburg, Germany, 2023 - [c8]Arnab Sharma, Vitalik Melnikov, Eyke Hüllermeier, Heike Wehrheim:
Property-Driven Black-Box Testing of Numeric Functions. Software Engineering 2023: 111-112 - 2022
- [c7]Arnab Sharma, Vitalik Melnikov, Eyke Hüllermeier, Heike Wehrheim:
Property-Driven Testing of Black-Box Functions. FormaliSE@ICSE 2022: 113-123 - 2021
- [c6]Arnab Sharma, Caglar Demir, Axel-Cyrille Ngonga Ngomo, Heike Wehrheim:
MLCHECK- Property-Driven Testing of Machine Learning Classifiers. ICMLA 2021: 738-745 - [i3]Arnab Sharma, Caglar Demir, Axel-Cyrille Ngonga Ngomo, Heike Wehrheim:
MLCheck- Property-Driven Testing of Machine Learning Models. CoRR abs/2105.00741 (2021) - 2020
- [c5]Arnab Sharma, Heike Wehrheim:
Higher income, larger loan? monotonicity testing of machine learning models. ISSTA 2020: 200-210 - [c4]Arnab Sharma, Heike Wehrheim:
Automatic Fairness Testing of Machine Learning Models. ICTSS 2020: 255-271 - [i2]Arnab Sharma, Heike Wehrheim:
Testing Monotonicity of Machine Learning Models. CoRR abs/2002.12278 (2020)
2010 – 2019
- 2019
- [c3]Arnab Sharma, Heike Wehrheim:
Testing Machine Learning Algorithms for Balanced Data Usage. ICST 2019: 125-135 - [c2]Stefan Schneider, Arnab Sharma, Holger Karl, Heike Wehrheim:
Specifying and Analyzing Virtual Network Services Using Queuing Petri Nets. IM 2019: 116-124 - [c1]Arnab Sharma, Heike Wehrheim:
Testing Balancedness of ML Algorithms. SE/SWM 2019: 157-158 - 2018
- [i1]Stefan Schneider, Arnab Sharma, Holger Karl, Heike Wehrheim:
Specifying and Analyzing Virtual Network Services Using Queuing Petri Nets. CoRR abs/1803.07007 (2018)
Coauthor Index
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