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cs.LG2026
Auditable Climate Risk Intelligence from Fragmented ESG Data: Deterministic Orchestration and Imbalance-Aware Learning for Scope 1-3 Validation
Karan Sehgal, Khawar Naveed Bhatti
ESG and climate risk data remain fragmented across heterogeneous Scope 1, Scope 2, and Scope 3 reporting environments, while conventional validation pipelines lack provenance aware…
cs.LG2026
Comparative Evaluation of Machine Learning Approaches for Minority-Class Financial Distress Prediction Under Class Imbalance Constraints
Karan Sehgal, Khawar Naveed Bhatti
Financial distress prediction remains a significant challenge in enterprise risk analysis due to the highly imbalanced nature of real-world financial datasets, where bankrupt or di…
cs.LG2020
MACE: Model Agnostic Concept Extractor for Explaining Image Classification Networks
Ashish Kumar, Karan Sehgal, Prerna Garg +2
Deep convolutional networks have been quite successful at various image classification tasks. The current methods to explain the predictions of a pre-trained model rely on gradient…